WorldWideScience

Sample records for rule based system

  1. Rule based deterioration identification and management system

    International Nuclear Information System (INIS)

    Kataoka, S.; Pavinich, W.; Lapides, M.

    1993-01-01

    Under the sponsorship of IHI and EPRI, a rule-based screening system has been developed that can be used by utility engineers to determine which deterioration mechanisms are acting on specific LWR components, and to evaluate the efficacy of an age-related deterioration management program. The screening system was developed using the rule-based shell, NEXPERT, which provides traceability to the data sources used in the logic development. The system addresses all the deterioration mechanisms of specific metals encountered in either BWRs or PWRs. Deterioration mechanisms are listed with reasons why they may occur during the design life of LWRs, considering the plant environment, manufacturing process, service history, material chemical composition, etc. of components in a specific location of a LWR. To eliminate the evaluation of inactive deterioration quickly, a tier structure is applied to the rules. The reasons why deterioration will occur are extracted automatically by backward chaining. To reduce the amount of user input, plant environmental data are stored in files as default environmental data. (author)

  2. Rule based systems for big data a machine learning approach

    CERN Document Server

    Liu, Han; Cocea, Mihaela

    2016-01-01

    The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

  3. Designing Fuzzy Rule Based Expert System for Cyber Security

    OpenAIRE

    Goztepe, Kerim

    2016-01-01

    The state of cyber security has begun to attract more attention and interest outside the community of computer security experts. Cyber security is not a single problem, but rather a group of highly different problems involving different sets of threats. Fuzzy Rule based system for cyber security is a system consists of a rule depository and a mechanism for accessing and running the rules. The depository is usually constructed with a collection of related rule sets. The aim of this study is to...

  4. Risk-based rules for crane safety systems

    Energy Technology Data Exchange (ETDEWEB)

    Ruud, Stian [Section for Control Systems, DNV Maritime, 1322 Hovik (Norway)], E-mail: Stian.Ruud@dnv.com; Mikkelsen, Age [Section for Lifting Appliances, DNV Maritime, 1322 Hovik (Norway)], E-mail: Age.Mikkelsen@dnv.com

    2008-09-15

    The International Maritime Organisation (IMO) has recommended a method called formal safety assessment (FSA) for future development of rules and regulations. The FSA method has been applied in a pilot research project for development of risk-based rules and functional requirements for systems and components for offshore crane systems. This paper reports some developments in the project. A method for estimating target reliability for the risk-control options (safety functions) by means of the cost/benefit decision criterion has been developed in the project and is presented in this paper. Finally, a structure for risk-based rules is proposed and presented.

  5. Risk-based rules for crane safety systems

    International Nuclear Information System (INIS)

    Ruud, Stian; Mikkelsen, Age

    2008-01-01

    The International Maritime Organisation (IMO) has recommended a method called formal safety assessment (FSA) for future development of rules and regulations. The FSA method has been applied in a pilot research project for development of risk-based rules and functional requirements for systems and components for offshore crane systems. This paper reports some developments in the project. A method for estimating target reliability for the risk-control options (safety functions) by means of the cost/benefit decision criterion has been developed in the project and is presented in this paper. Finally, a structure for risk-based rules is proposed and presented

  6. A Belief Rule-Based Expert System to Diagnose Influenza

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Khalid, Md. Saifuddin; Akter, Shamima

    2014-01-01

    , development and application of an expert system to diagnose influenza under uncertainty. The recently developed generic belief rule-based inference methodology by using the evidential reasoning (RIMER) approach is employed to develop this expert system, termed as Belief Rule Based Expert System (BRBES......). The RIMER approach can handle different types of uncertainties, both in knowledge representation, and in inference procedures. The knowledge-base of this system was constructed by using records of the real patient data along with in consultation with the Influenza specialists of Bangladesh. Practical case...

  7. An Embedded Rule-Based Diagnostic Expert System in Ada

    Science.gov (United States)

    Jones, Robert E.; Liberman, Eugene M.

    1992-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  8. COLLABORATIVE NETWORK SECURITY MANAGEMENT SYSTEM BASED ON ASSOCIATION MINING RULE

    Directory of Open Access Journals (Sweden)

    Nisha Mariam Varughese

    2014-07-01

    Full Text Available Security is one of the major challenges in open network. There are so many types of attacks which follow fixed patterns or frequently change their patterns. It is difficult to find the malicious attack which does not have any fixed patterns. The Distributed Denial of Service (DDoS attacks like Botnets are used to slow down the system performance. To address such problems Collaborative Network Security Management System (CNSMS is proposed along with the association mining rule. CNSMS system is consists of collaborative Unified Threat Management (UTM, cloud based security centre and traffic prober. The traffic prober captures the internet traffic and given to the collaborative UTM. Traffic is analysed by the Collaborative UTM, to determine whether it contains any malicious attack or not. If any security event occurs, it will reports to the cloud based security centre. The security centre generates security rules based on association mining rule and distributes to the network. The cloud based security centre is used to store the huge amount of tragic, their logs and the security rule generated. The feedback is evaluated and the invalid rules are eliminated to improve the system efficiency.

  9. Hierarchical graphs for rule-based modeling of biochemical systems

    Directory of Open Access Journals (Sweden)

    Hu Bin

    2011-02-01

    Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for

  10. A rule-based smart automated fertilization and irrigation systems

    Science.gov (United States)

    Yousif, Musab El-Rashid; Ghafar, Khairuddin; Zahari, Rahimi; Lim, Tiong Hoo

    2018-04-01

    Smart automation in industries has become very important as it can improve the reliability and efficiency of the systems. The use of smart technologies in agriculture have increased over the year to ensure and control the production of crop and address food security. However, it is important to use proper irrigation systems avoid water wastage and overfeeding of the plant. In this paper, a Smart Rule-based Automated Fertilization and Irrigation System is proposed and evaluated. We propose a rule based decision making algorithm to monitor and control the food supply to the plant and the soil quality. A build-in alert system is also used to update the farmer using a text message. The system is developed and evaluated using a real hardware.

  11. Online Dispatching Rules For Vehicle-Based Internal Transport Systems

    NARCIS (Netherlands)

    T. Le-Anh (Tuan); M.B.M. de Koster (René)

    2004-01-01

    textabstractOn-line vehicles dispatching rules are widely used in many facilities such as warehouses to control vehicles' movements. Single-attribute dispatching rules, which dispatch vehicles based on only one parameter, are used commonly. However, multi-attribute dispatching rules prove to be

  12. Genetic learning in rule-based and neural systems

    Science.gov (United States)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  13. Rule - based Fault Diagnosis Expert System for Wind Turbine

    Directory of Open Access Journals (Sweden)

    Deng Xiao-Wen

    2017-01-01

    Full Text Available Under the trend of increasing installed capacity of wind power, the intelligent fault diagnosis of wind turbine is of great significance to the safe and efficient operation of wind farms. Based on the knowledge of fault diagnosis of wind turbines, this paper builds expert system diagnostic knowledge base by using confidence production rules and expert system self-learning method. In Visual Studio 2013 platform, C # language is selected and ADO.NET technology is used to access the database. Development of Fault Diagnosis Expert System for Wind Turbine. The purpose of this paper is to realize on-line diagnosis of wind turbine fault through human-computer interaction, and to improve the diagnostic capability of the system through the continuous improvement of the knowledge base.

  14. Uncertain rule-based fuzzy systems introduction and new directions

    CERN Document Server

    Mendel, Jerry M

    2017-01-01

    The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy se...

  15. Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

    Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

  16. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Directory of Open Access Journals (Sweden)

    Yaacob Sazali

    2005-01-01

    Full Text Available We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI system. The NAVI has a single board processing system (SBPS, a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  17. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Science.gov (United States)

    Nagarajan, R.; Sainarayanan, G.; Yaacob, Sazali; Porle, Rosalyn R.

    2005-12-01

    We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI) system. The NAVI has a single board processing system (SBPS), a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  18. Rule-based expert system for maritime anomaly detection

    Science.gov (United States)

    Roy, Jean

    2010-04-01

    Maritime domain operators/analysts have a mandate to be aware of all that is happening within their areas of responsibility. This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc., and it has become more challenging in the past decade, as commercial shipping turned into a potential threat. In particular, a huge portion of the data and information made available to the operators/analysts is mundane, from maritime platforms going about normal, legitimate activities, and it is very challenging for them to detect and identify the non-mundane. To achieve such anomaly detection, they must establish numerous relevant situational facts from a variety of sensor data streams. Unfortunately, many of the facts of interest just cannot be observed; the operators/analysts thus use their knowledge of the maritime domain and their reasoning faculties to infer these facts. As they are often overwhelmed by the large amount of data and information, automated reasoning tools could be used to support them by inferring the necessary facts, ultimately providing indications and warning on a small number of anomalous events worthy of their attention. Along this line of thought, this paper describes a proof-of-concept prototype of a rule-based expert system implementing automated rule-based reasoning in support of maritime anomaly detection.

  19. A new type of simplified fuzzy rule-based system

    Science.gov (United States)

    Angelov, Plamen; Yager, Ronald

    2012-02-01

    Over the last quarter of a century, two types of fuzzy rule-based (FRB) systems dominated, namely Mamdani and Takagi-Sugeno type. They use the same type of scalar fuzzy sets defined per input variable in their antecedent part which are aggregated at the inference stage by t-norms or co-norms representing logical AND/OR operations. In this paper, we propose a significantly simplified alternative to define the antecedent part of FRB systems by data Clouds and density distribution. This new type of FRB systems goes further in the conceptual and computational simplification while preserving the best features (flexibility, modularity, and human intelligibility) of its predecessors. The proposed concept offers alternative non-parametric form of the rules antecedents, which fully reflects the real data distribution and does not require any explicit aggregation operations and scalar membership functions to be imposed. Instead, it derives the fuzzy membership of a particular data sample to a Cloud by the data density distribution of the data associated with that Cloud. Contrast this to the clustering which is parametric data space decomposition/partitioning where the fuzzy membership to a cluster is measured by the distance to the cluster centre/prototype ignoring all the data that form that cluster or approximating their distribution. The proposed new approach takes into account fully and exactly the spatial distribution and similarity of all the real data by proposing an innovative and much simplified form of the antecedent part. In this paper, we provide several numerical examples aiming to illustrate the concept.

  20. Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

    Science.gov (United States)

    Hinchey, Mike; Rash, James; Erickson, John; Gracanin, Denis; Rouff, Chris

    2010-01-01

    Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

  1. Strategy-Driven Exploration for Rule-Based Models of Biochemical Systems with Porgy

    OpenAIRE

    Andrei , Oana; Fernández , Maribel; Kirchner , Hélène; Pinaud , Bruno

    2016-01-01

    This paper presents Porgy – an interactive visual environment for rule-based modelling of biochemical systems. We model molecules and molecule interactions as port graphs and port graph rewrite rules, respectively. We use rewriting strategies to control which rules to apply, and where and when to apply them. Our main contributions to rule-based modelling of biochemical systems lie in the strategy language and the associated visual and interactive features offered by Porgy. These features faci...

  2. Declarative Rule-based Safety for Robotic Perception Systems

    DEFF Research Database (Denmark)

    Mogensen, Johann Thor Ingibergsson; Kraft, Dirk; Schultz, Ulrik Pagh

    2017-01-01

    Mobile robots are used across many domains from personal care to agriculture. Working in dynamic open-ended environments puts high constraints on the robot perception system, which is critical for the safety of the system as a whole. To achieve the required safety levels the perception system needs...... to be certified, but no specific standards exist for computer vision systems, and the concept of safe vision systems remains largely unexplored. In this paper we present a novel domain-specific language that allows the programmer to express image quality detection rules for enforcing safety constraints...

  3. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  4. Design of a Fuzzy Rule Base Expert System to Predict and Classify ...

    African Journals Online (AJOL)

    The main objective of design of a rule base expert system using fuzzy logic approach is to predict and forecast the risk level of cardiac patients to avoid sudden death. In this proposed system, uncertainty is captured using rule base and classification using fuzzy c-means clustering is discussed to overcome the risk level, ...

  5. An evaluation and implementation of rule-based Home Energy Management System using the Rete algorithm.

    Science.gov (United States)

    Kawakami, Tomoya; Fujita, Naotaka; Yoshihisa, Tomoki; Tsukamoto, Masahiko

    2014-01-01

    In recent years, sensors become popular and Home Energy Management System (HEMS) takes an important role in saving energy without decrease in QoL (Quality of Life). Currently, many rule-based HEMSs have been proposed and almost all of them assume "IF-THEN" rules. The Rete algorithm is a typical pattern matching algorithm for IF-THEN rules. Currently, we have proposed a rule-based Home Energy Management System (HEMS) using the Rete algorithm. In the proposed system, rules for managing energy are processed by smart taps in network, and the loads for processing rules and collecting data are distributed to smart taps. In addition, the number of processes and collecting data are reduced by processing rules based on the Rete algorithm. In this paper, we evaluated the proposed system by simulation. In the simulation environment, rules are processed by a smart tap that relates to the action part of each rule. In addition, we implemented the proposed system as HEMS using smart taps.

  6. Rule-based topology system for spatial databases to validate complex geographic datasets

    Science.gov (United States)

    Martinez-Llario, J.; Coll, E.; Núñez-Andrés, M.; Femenia-Ribera, C.

    2017-06-01

    A rule-based topology software system providing a highly flexible and fast procedure to enforce integrity in spatial relationships among datasets is presented. This improved topology rule system is built over the spatial extension Jaspa. Both projects are open source, freely available software developed by the corresponding author of this paper. Currently, there is no spatial DBMS that implements a rule-based topology engine (considering that the topology rules are designed and performed in the spatial backend). If the topology rules are applied in the frontend (as in many GIS desktop programs), ArcGIS is the most advanced solution. The system presented in this paper has several major advantages over the ArcGIS approach: it can be extended with new topology rules, it has a much wider set of rules, and it can mix feature attributes with topology rules as filters. In addition, the topology rule system can work with various DBMSs, including PostgreSQL, H2 or Oracle, and the logic is performed in the spatial backend. The proposed topology system allows users to check the complex spatial relationships among features (from one or several spatial layers) that require some complex cartographic datasets, such as the data specifications proposed by INSPIRE in Europe and the Land Administration Domain Model (LADM) for Cadastral data.

  7. Domain-based Teaching Strategy for Intelligent Tutoring System Based on Generic Rules

    Science.gov (United States)

    Kseibat, Dawod; Mansour, Ali; Adjei, Osei; Phillips, Paul

    In this paper we present a framework for selecting the proper instructional strategy for a given teaching material based on its attributes. The new approach is based on a flexible design by means of generic rules. The framework was adapted in an Intelligent Tutoring System to teach Modern Standard Arabic language to adult English-speaking learners with no pre-knowledge of Arabic language is required.

  8. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  9. A self-learning rule base for command following in dynamical systems

    Science.gov (United States)

    Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

    1992-01-01

    In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

  10. Research on key technology of the verification system of steel rule based on vision measurement

    Science.gov (United States)

    Jia, Siyuan; Wang, Zhong; Liu, Changjie; Fu, Luhua; Li, Yiming; Lu, Ruijun

    2018-01-01

    The steel rule plays an important role in quantity transmission. However, the traditional verification method of steel rule based on manual operation and reading brings about low precision and low efficiency. A machine vison based verification system of steel rule is designed referring to JJG1-1999-Verificaiton Regulation of Steel Rule [1]. What differentiates this system is that it uses a new calibration method of pixel equivalent and decontaminates the surface of steel rule. Experiments show that these two methods fully meet the requirements of the verification system. Measuring results strongly prove that these methods not only meet the precision of verification regulation, but also improve the reliability and efficiency of the verification system.

  11. Rule base system in developing groundwater pollution expert system: predicting model

    International Nuclear Information System (INIS)

    Mongkon Ta-oun; Mohamed Daud; Mohd Zohadie Bardaie; Shamshuddin Jusop

    2000-01-01

    New techniques are now available for use in the protection of the environment. One of these techniques is the use of expert system for prediction groundwater pollution potential. Groundwater Pollution Expert system (GWPES) rules are a collection of principles and procedures used to know the comprehension of groundwater pollution prediction. The rules of groundwater pollution expert system in the form of questions, choice, radio-box, slide rule, button or frame are translated in to IF-THEN rule. The rules including of variables, types, domains and descriptions were used by the function of wxCLIPS (C Language Integrate Production System) expert system shell. (author)

  12. A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Hossain, Emran; Khalid, Md. Saifuddin

    2014-01-01

    conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation...... and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system....

  13. Diversity of Rule-based Approaches: Classic Systems and Recent Applications

    Directory of Open Access Journals (Sweden)

    Grzegorz J. Nalepa

    2016-11-01

    Full Text Available Rules are a common symbolic model of knowledge. Rule-based systems share roots in cognitive science and artificial intelligence. In the former, they are mostly used in cognitive architectures; in the latter, they are developed in several domains including knowledge engineering and machine learning. This paper aims to give an overview of these issues with the focus on the current research perspective of artificial intelligence. Moreover, in this setting we discuss our results in the design of rule-based systems and their applications in context-aware and business intelligence systems.

  14. A RULE-BASED SYSTEM APPROACH FOR SAFETY MANAGEMENT IN HAZARDOUS WORK SYSTEMS

    Directory of Open Access Journals (Sweden)

    Ercüment N. DİZDAR

    1998-03-01

    Full Text Available Developments in technology increased the importance of safety management in work life. These improvements also resulted in a requirement of more investment and assignment on human in work systems. Here we face this problem: Can we make it possible to forecast the possible accidents that workers can face, and prevent these accidents by taking necessary precautions? In this study made, we aimed at developing an rule-based system to forecast the occupational accidents in coming periods at the departments of the facilities in hazardous work systems. The validity of the developed system was proved by implementing it into practice in hazardous work systems in manufacturing industry.

  15. Rule-Based Analytic Asset Management for Space Exploration Systems (RAMSES), Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Payload Systems Inc. (PSI) and the Massachusetts Institute of Technology (MIT) were selected to jointly develop the Rule-based Analytic Asset Management for Space...

  16. A Fuzzy Rule-Based Expert System for Evaluating Intellectual Capital

    Directory of Open Access Journals (Sweden)

    Mohammad Hossein Fazel Zarandi

    2012-01-01

    Full Text Available A fuzzy rule-based expert system is developed for evaluating intellectual capital. A fuzzy linguistic approach assists managers to understand and evaluate the level of each intellectual capital item. The proposed fuzzy rule-based expert system applies fuzzy linguistic variables to express the level of qualitative evaluation and criteria of experts. Feasibility of the proposed model is demonstrated by the result of intellectual capital performance evaluation for a sample company.

  17. Organizational Knowledge Transfer Using Ontologies and a Rule-Based System

    Science.gov (United States)

    Okabe, Masao; Yoshioka, Akiko; Kobayashi, Keido; Yamaguchi, Takahira

    In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

  18. A Web-Based Rice Plant Expert System Using Rule-Based Reasoning

    Directory of Open Access Journals (Sweden)

    Anton Setiawan Honggowibowo

    2009-12-01

    Full Text Available Rice plants can be attacked by various kinds of diseases which are possible to be determined from their symptoms. However, it is to recognize that to find out the exact type of disease, an agricultural expert’s opinion is needed, meanwhile the numbers of agricultural experts are limited and there are too many problems to be solved at the same time. This makes a system with a capability as an expert is required. This system must contain the knowledge of the diseases and symptom of rice plants as an agricultural expert has to have. This research designs a web-based expert system using rule-based reasoning. The rule are modified from the method of forward chaining inference and backward chaining in order to to help farmers in the rice plant disease diagnosis. The web-based rice plants disease diagnosis expert system has the advantages to access and use easily. With web-based features inside, it is expected that the farmer can accesse the expert system everywhere to overcome the problem to diagnose rice diseases.

  19. Implementasi Rule Based Expert Systems untuk Realtime Monitoring Penyelesaian Perkara Pidana Menggunakan Teknologi Radio Frequency Identification

    Directory of Open Access Journals (Sweden)

    Mar Fuah

    2017-05-01

    Full Text Available One of the problems in the criminal case completions is that the difficulty of making decision to estimate when the settlement of the case file will be fulfilled. It is caused by the number of case files handled and detention time changing. Therefore, the fast and accurate information is needed. The research aims to develop a monitoring system tracking and tracking of scheduling rules using Rule Based Expert Systems method with 17 rules, and supported by Radio Frequency Identification technology (RFID in the form of computer applications. Based on the output of the system, an analysis is performed in the criminal case settlement process with a set of IF-THEN rules. The RFID reader read the data of case files through radio wave signals emitted by the antenna toward active-Tag attached in the criminal case file. The system is designed to monitor the tracking and tracing of RFID-based scheduling rules in realtime way that was built in the form of computer application in accordance with the system design. This study results in no failure in reading active tags by the RFID reader to detect criminal case files that had been examined. There were many case files handled in three different location, they were the constabulary, prosecutor, and judges of district court and RFID was able to identify them simultaneously. So, RFID supports the implementation of Rule Based Expert Systems very much for realtime monitoring in criminal case accomplishment.

  20. Development of a rule-based diagnostic platform on an object-oriented expert system shell

    International Nuclear Information System (INIS)

    Wang, Wenlin; Yang, Ming; Seong, Poong Hyun

    2016-01-01

    Highlights: • Multilevel Flow Model represents system knowledge as a domain map in expert system. • Rule-based fault diagnostic expert system can identify root cause via a causal chain. • Rule-based fault diagnostic expert system can be used for fault simulation training. - Abstract: This paper presents the development and implementation of a real-time rule-based diagnostic platform. The knowledge is acquired from domain experts and textbooks and the design of the fault diagnosis expert system was performed in the following ways: (i) establishing of corresponding classes and instances to build the domain map, (ii) creating of generic fault models based on events, and (iii) building of diagnostic reasoning based on rules. Knowledge representation is a complicated issue of expert systems. One highlight of this paper is that the Multilevel Flow Model has been used to represent the knowledge, which composes the domain map within the expert system as well as providing a concise description of the system. The developed platform is illustrated using the pressure safety system of a pressurized water reactor as an example of the simulation test bed; the platform is developed using the commercial and industrially validated software G2. The emulation test was conducted and it has been proven that the fault diagnosis expert system can identify the faults correctly and in a timely way; this system can be used as a simulation-based training tool to assist operators to make better decisions.

  1. Techniques and implementation of the embedded rule-based expert system using Ada

    Science.gov (United States)

    Liberman, Eugene M.; Jones, Robert E.

    1991-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  2. Automated implementation of rule-based expert systems with neural networks for time-critical applications

    Science.gov (United States)

    Ramamoorthy, P. A.; Huang, Song; Govind, Girish

    1991-01-01

    In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

  3. Evolving rule-based systems in two medical domains using genetic programming.

    Science.gov (United States)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

    2004-11-01

    To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

  4. AN QUALITY BASED ENHANCEMENT OF USER DATA PROTECTION VIA FUZZY RULE BASED SYSTEMS IN CLOUD ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    R Poorva Devi

    2016-04-01

    Full Text Available So far, in cloud computing distinct customer is accessed and consumed enormous amount of services through web, offered by cloud service provider (CSP. However cloud is providing one of the services is, security-as-a-service to its clients, still people are terrified to use the service from cloud vendor. Number of solutions, security components and measurements are coming with the new scope for the cloud security issue, but 79.2% security outcome only obtained from the different scientists, researchers and other cloud based academy community. To overcome the problem of cloud security the proposed model that is, “Quality based Enhancing the user data protection via fuzzy rule based systems in cloud environment”, will helps to the cloud clients by the way of accessing the cloud resources through remote monitoring management (RMMM and what are all the services are currently requesting and consuming by the cloud users that can be well analyzed with Managed service provider (MSP rather than a traditional CSP. Normally, people are trying to secure their own private data by applying some key management and cryptographic based computations again it will direct to the security problem. In order to provide good quality of security target result by making use of fuzzy rule based systems (Constraint & Conclusion segments in cloud environment. By using this technique, users may obtain an efficient security outcome through the cloud simulation tool of Apache cloud stack simulator.

  5. TRICARE revision to CHAMPUS DRG-based payment system, pricing of hospital claims. Final rule.

    Science.gov (United States)

    2014-05-21

    This Final rule changes TRICARE's current regulatory provision for inpatient hospital claims priced under the DRG-based payment system. Claims are currently priced by using the rates and weights that are in effect on a beneficiary's date of admission. This Final rule changes that provision to price such claims by using the rates and weights that are in effect on a beneficiary's date of discharge.

  6. Using an improved association rules mining optimization algorithm in web-based mobile-learning system

    Science.gov (United States)

    Huang, Yin; Chen, Jianhua; Xiong, Shaojun

    2009-07-01

    Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

  7. Sistem Evaluasi Jamunan Mutu Menggunakan Rule Based System Untuk Monitoring Mutu Perguruan Tinggi

    Directory of Open Access Journals (Sweden)

    Sri Hartono

    2017-05-01

    Full Text Available The needs for continuous quality improvement resulting in the more complex. The research aims to develop system of quality assurance evaluation using rule based system to monitor the quality of higher education. This process of the research begins by documenting the daily activity of study program which consists of lecturer data, research data, service data, staff data, student data, and infrastructure data into a database. The data were evaluated by using rule based system  by adopting rules on quality standards of study program of National Accreditation Board for Higher Education as the knowledge base. Evaluation process was carried out by using the forward chaining methods by matching the existing data to the knowledge base to determine the quality status of each quality standard. While the reccomendation process was carried out by using the backward chaining methods by matching the results of quality status to the desired projection of quality status to determine the nearest target which can be achieved. The result of the research is system of quality assurance evaluation with rule based system that is capable of producing an output system in the form of internal evaluation report and recommendation system that can be used to monitor the quality of higher education.

  8. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

    Science.gov (United States)

    Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

    2013-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

  9. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

    Science.gov (United States)

    Chylek, Lily A; Harris, Leonard A; Tung, Chang-Shung; Faeder, James R; Lopez, Carlos F; Hlavacek, William S

    2014-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). © 2013 Wiley Periodicals, Inc.

  10. ABOUT CLINICAL EXPERT SYSTEM BASED ON RULES USING DATA MINING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    V. P. Martsenyuk

    2015-05-01

    Full Text Available In the work the topics of software implementation of rule induction method based on sequential covering algorithm are considered. Such approach allows us to develop clinical decision support system. The project is implemented within Netbeans IDE based on Java-classes.

  11. Challenges for Rule Systems on the Web

    Science.gov (United States)

    Hu, Yuh-Jong; Yeh, Ching-Long; Laun, Wolfgang

    The RuleML Challenge started in 2007 with the objective of inspiring the issues of implementation for management, integration, interoperation and interchange of rules in an open distributed environment, such as the Web. Rules are usually classified as three types: deductive rules, normative rules, and reactive rules. The reactive rules are further classified as ECA rules and production rules. The study of combination rule and ontology is traced back to an earlier active rule system for relational and object-oriented (OO) databases. Recently, this issue has become one of the most important research problems in the Semantic Web. Once we consider a computer executable policy as a declarative set of rules and ontologies that guides the behavior of entities within a system, we have a flexible way to implement real world policies without rewriting the computer code, as we did before. Fortunately, we have de facto rule markup languages, such as RuleML or RIF to achieve the portability and interchange of rules for different rule systems. Otherwise, executing real-life rule-based applications on the Web is almost impossible. Several commercial or open source rule engines are available for the rule-based applications. However, we still need a standard rule language and benchmark for not only to compare the rule systems but also to measure the progress in the field. Finally, a number of real-life rule-based use cases will be investigated to demonstrate the applicability of current rule systems on the Web.

  12. Ant-based extraction of rules in simple decision systems over ontological graphs

    Directory of Open Access Journals (Sweden)

    Pancerz Krzysztof

    2015-06-01

    Full Text Available In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominancebased rough set approach (DRSA. In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems

  13. A Belief Rule Based Expert System to Assess Mental Disorder under Uncertainty

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Afif Monrat, Ahmed; Hasan, Mamun

    2016-01-01

    to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema......Mental disorder is a change of mental or behavioral pattern that causes sufferings and impairs the ability to function in ordinary life. In psychopathology, the assessment methods of mental disorder contain various types of uncertainties associated with signs and symptoms. This study identifies...

  14. Generation of facial expressions from emotion using a fuzzy rule based system

    NARCIS (Netherlands)

    Bui, T.D.; Heylen, Dirk K.J.; Poel, Mannes; Nijholt, Antinus; Stumptner, Markus; Corbett, Dan; Brooks, Mike

    2001-01-01

    We propose a fuzzy rule-based system to map representations of the emotional state of an animated agent onto muscle contraction values for the appropriate facial expressions. Our implementation pays special attention to the way in which continuous changes in the intensity of emotions can be

  15. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...

  16. Belief-rule-based expert systems for evaluation of e-government

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Zander, Pär-Ola Mikael; Kamal, Md Sarwar

    2015-01-01

    , known as the Belief Rule Based Expert System (BRBES) and implemented in the local e-government of Bangladesh. The results have been compared with a recently developed method of evaluating e-government, and it is demonstrated that the results of the BRBES are more accurate and reliable. The BRBES can...

  17. Capacities and overlap indexes with an application in fuzzy rule-based classification systems

    Czech Academy of Sciences Publication Activity Database

    Paternain, D.; Bustince, H.; Pagola, M.; Sussner, P.; Kolesárová, A.; Mesiar, Radko

    2016-01-01

    Roč. 305, č. 1 (2016), s. 70-94 ISSN 0165-0114 Institutional support: RVO:67985556 Keywords : Capacity * Overlap index * Overlap function * Choquet integral * Fuzzy rule-based classification systems Subject RIV: BA - General Mathematics Impact factor: 2.718, year: 2016 http://library.utia.cas.cz/separaty/2016/E/mesiar-0465739.pdf

  18. An expert system design to diagnose cancer by using a new method reduced rule base.

    Science.gov (United States)

    Başçiftçi, Fatih; Avuçlu, Emre

    2018-04-01

    A Medical Expert System (MES) was developed which uses Reduced Rule Base to diagnose cancer risk according to the symptoms in an individual. A total of 13 symptoms were used. With the new MES, the reduced rules are controlled instead of all possibilities (2 13 = 8192 different possibilities occur). By controlling reduced rules, results are found more quickly. The method of two-level simplification of Boolean functions was used to obtain Reduced Rule Base. Thanks to the developed application with the number of dynamic inputs and outputs on different platforms, anyone can easily test their own cancer easily. More accurate results were obtained considering all the possibilities related to cancer. Thirteen different risk factors were determined to determine the type of cancer. The truth table produced in our study has 13 inputs and 4 outputs. The Boolean Function Minimization method is used to obtain less situations by simplifying logical functions. Diagnosis of cancer quickly thanks to control of the simplified 4 output functions. Diagnosis made with the 4 output values obtained using Reduced Rule Base was found to be quicker than diagnosis made by screening all 2 13 = 8192 possibilities. With the improved MES, more probabilities were added to the process and more accurate diagnostic results were obtained. As a result of the simplification process in breast and renal cancer diagnosis 100% diagnosis speed gain, in cervical cancer and lung cancer diagnosis rate gain of 99% was obtained. With Boolean function minimization, less number of rules is evaluated instead of evaluating a large number of rules. Reducing the number of rules allows the designed system to work more efficiently and to save time, and facilitates to transfer the rules to the designed Expert systems. Interfaces were developed in different software platforms to enable users to test the accuracy of the application. Any one is able to diagnose the cancer itself using determinative risk factors. Thereby

  19. A rule-based computer control system for PBX-M neutral beams

    International Nuclear Information System (INIS)

    Frank, K.T.; Kozub, T.A.; Kugel, H.W.

    1987-01-01

    The Princeton Beta Experiment (PBX) neutral beams have been routinely operated under automatic computer control. A major upgrade of the computer configuration was undertaken to coincide with the PBX machine modification. The primary tasks included in the computer control system are data acquisition, waveform reduction, automatic control and data storage. The portion of the system which will remain intact is the rule-based approach to automatic control. Increased computational and storage capability will allow the expansion of the knowledge base previously used. The hardware configuration supported by the PBX Neutral Beam (XNB) software includes a dedicated Microvax with five CAMAC crates and four process controllers. The control algorithms are rule-based and goal-driven. The automatic control system raises ion source electrical parameters to selected energy goals and maintains these levels until new goals are requested or faults are detected

  20. An Expert System for Diagnosis of Sleep Disorder Using Fuzzy Rule-Based Classification Systems

    Science.gov (United States)

    Septem Riza, Lala; Pradini, Mila; Fitrajaya Rahman, Eka; Rasim

    2017-03-01

    Sleep disorder is an anomaly that could cause problems for someone’ sleeping pattern. Nowadays, it becomes an issue since people are getting busy with their own business and have no time to visit the doctors. Therefore, this research aims to develop a system used for diagnosis of sleep disorder using Fuzzy Rule-Based Classification System (FRBCS). FRBCS is a method based on the fuzzy set concepts. It consists of two steps: (i) constructing a model/knowledge involving rulebase and database, and (ii) prediction over new data. In this case, the knowledge is obtained from experts whereas in the prediction stage, we perform fuzzification, inference, and classification. Then, a platform implementing the method is built with a combination between PHP and the R programming language using the “Shiny” package. To validate the system that has been made, some experiments have been done using data from a psychiatric hospital in West Java, Indonesia. Accuracy of the result and computation time are 84.85% and 0.0133 seconds, respectively.

  1. Integration of object-oriented knowledge representation with the CLIPS rule based system

    Science.gov (United States)

    Logie, David S.; Kamil, Hasan

    1990-01-01

    The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

  2. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    Directory of Open Access Journals (Sweden)

    C. Boldisor

    2009-12-01

    Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.

  3. Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID

    Directory of Open Access Journals (Sweden)

    Ardhyanti Mita Nugraha Joanna

    2018-01-01

    Full Text Available Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP. This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

  4. Towards a framework for threaded inference in rule-based systems

    Directory of Open Access Journals (Sweden)

    Luis Casillas Santillan

    2013-11-01

    Full Text Available nformation and communication technologies have shown a significant advance and fast pace in their performance and pervasiveness. Knowledge has become a significant asset for organizations, which need to deal with large amounts of data and information to produce valuable knowledge. Dealing with knowledge is turning the axis for organizations in the new economy. One of the choices to gather the goal of knowledge managing is the use of rule-based systems. This kind of approach is the new chance for expert-systems’ technology. Modern languages and cheap computing allow the implementation of concurrent systems for dealing huge volumes of information in organizations. The present work is aimed at proposing the use of contemporary programming elements, as easy to exploit threading, when implementing rule-based treatment over huge data volumes.

  5. Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID)

    Science.gov (United States)

    Nugraha, Joanna Ardhyanti Mita; Suryono; Suseno, dan Jatmiko Endro

    2018-02-01

    Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID) as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP). This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

  6. A Belief Rule-Based Expert System to Assess Bronchiolitis Suspicion from Signs and Symptoms Under Uncertainty

    DEFF Research Database (Denmark)

    Karim, Rezuan; Hossain, Mohammad Shahadat; Khalid, Md. Saifuddin

    2017-01-01

    developed generic belief rule-based inference methodology by using evidential reasoning (RIMER) acts as the inference engine of this BRBES while belief rule base as the knowledge representation schema. The knowledge base of the system is constructed by using real patient data and expert opinion from...

  7. Knowledge Representation and Inference for Analysis and Design of Database and Tabular Rule-Based Systems

    Directory of Open Access Journals (Sweden)

    Antoni Ligeza

    2001-01-01

    Full Text Available Rulebased systems constitute a powerful tool for specification of knowledge in design and implementation of knowledge based systems. They provide also a universal programming paradigm for domains such as intelligent control, decision support, situation classification and operational knowledge encoding. In order to assure safe and reliable performance, such system should satisfy certain formal requirements, including completeness and consistency. This paper addresses the issue of analysis and verification of selected properties of a class of such system in a systematic way. A uniform, tabular scheme of single-level rule-based systems is considered. Such systems can be applied as a generalized form of databases for specification of data pattern (unconditional knowledge, or can be used for defining attributive decision tables (conditional knowledge in form of rules. They can also serve as lower-level components of a hierarchical multi-level control and decision support knowledge-based systems. An algebraic knowledge representation paradigm using extended tabular representation, similar to relational database tables is presented and algebraic bases for system analysis, verification and design support are outlined.

  8. LPS: a rule-based, schema-oriented knowledge representation system

    Energy Technology Data Exchange (ETDEWEB)

    Anzai, Y; Mitsuya, Y; Nakajima, S; Ura, S

    1981-01-01

    A new knowledge representation system called LPS is presented. The global control structure of LPS is rule-based, but the local representational structure is schema-oriented. The present version of LPS was designed to increase the understandability of representation while keeping time efficiency reasonable. Pattern matching through slot-networks and meta-actions from among the implemented facilities of LPS, are especially described in detail. 7 references.

  9. Considerations Regarding the Expert Systems in the Economy and the Use Method of the Production Systems Based on Rules

    Directory of Open Access Journals (Sweden)

    Eugenia IANCU

    2010-01-01

    Full Text Available As it is known, the expert systems- particularlyreferring to the ones in the economical area, represent a currentissue of our days, them being approached by all the economicalbranches. Starting from these aspects, we wish to present somenecessary principles and considerations regarding the expertsystems, representation of the facts, systems based onproduction rules. The objective of this paper is aimed toidentifying the exigencies of the production system based onrules.

  10. Methodological approaches based on business rules

    Directory of Open Access Journals (Sweden)

    Anca Ioana ANDREESCU

    2008-01-01

    Full Text Available Business rules and business processes are essential artifacts in defining the requirements of a software system. Business processes capture business behavior, while rules connect processes and thus control processes and business behavior. Traditionally, rules are scattered inside application code. This approach makes it very difficult to change rules and shorten the life cycle of the software system. Because rules change more quickly than the application itself, it is desirable to externalize the rules and move them outside the application. This paper analyzes and evaluates three well-known business rules approaches. It also outlines some critical factors that have to be taken into account in the decision to introduce business rules facilities in a software system. Based on the concept of explicit manipulation of business rules in a software system, the need for a general approach based on business rules is discussed.

  11. Merit-Based Incentive Payment System: Meaningful Changes in the Final Rule Brings Cautious Optimism.

    Science.gov (United States)

    Manchikanti, Laxmaiah; Helm Ii, Standiford; Calodney, Aaron K; Hirsch, Joshua A

    2017-01-01

    The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) eliminated the flawed Sustainable Growth Rate (SGR) act formula - a longstanding crucial issue of concern for health care providers and Medicare beneficiaries. MACRA also included a quality improvement program entitled, "The Merit-Based Incentive Payment System, or MIPS." The proposed rule of MIPS sought to streamline existing federal quality efforts and therefore linked 4 distinct programs into one. Three existing programs, meaningful use (MU), Physician Quality Reporting System (PQRS), value-based payment (VBP) system were merged with the addition of Clinical Improvement Activity category. The proposed rule also changed the name of MU to Advancing Care Information, or ACI. ACI contributes to 25% of composite score of the four programs, PQRS contributes 50% of the composite score, while VBP system, which deals with resource use or cost, contributes to 10% of the composite score. The newest category, Improvement Activities or IA, contributes 15% to the composite score. The proposed rule also created what it called a design incentive that drives movement to delivery system reform principles with the inclusion of Advanced Alternative Payment Models (APMs).Following the release of the proposed rule, the medical community, as well as Congress, provided substantial input to Centers for Medicare and Medicaid Services (CMS),expressing their concern. American Society of Interventional Pain Physicians (ASIPP) focused on 3 important aspects: delay the implementation, provide a 3-month performance period, and provide ability to submit meaningful quality measures in a timely and economic manner. The final rule accepted many of the comments from various organizations, including several of those specifically emphasized by ASIPP, with acceptance of 3-month reporting period, as well as the ability to submit non-MIPS measures to improve real quality and make the system meaningful. CMS also provided a mechanism for

  12. Rule-Based Event Processing and Reaction Rules

    Science.gov (United States)

    Paschke, Adrian; Kozlenkov, Alexander

    Reaction rules and event processing technologies play a key role in making business and IT / Internet infrastructures more agile and active. While event processing is concerned with detecting events from large event clouds or streams in almost real-time, reaction rules are concerned with the invocation of actions in response to events and actionable situations. They state the conditions under which actions must be taken. In the last decades various reaction rule and event processing approaches have been developed, which for the most part have been advanced separately. In this paper we survey reaction rule approaches and rule-based event processing systems and languages.

  13. The development of cause analysis system for CPCS trip using the rule-base deduction

    International Nuclear Information System (INIS)

    Park, Hee Seok; Kim, Dong Hoon; Seo, Ho Joon; Koo, In Soo; Park, Suk Joon

    1992-01-01

    The Core Protection Calculator System(CPCS) was developed to initiate a Reactor Trip under the circumstance of certain transients by Combustion Engineering Company. The major function of the CPCS is to generate contact outputs for the Departure from Nucleate Boiling Ratio(DNBR) Trip and Local Power Density(LPD) Trip. But in CPCS the trip causes can not be identified, only trip status is displayed. It may take much time and efforts for plant operator to analyse the trip causes of CPCS. So, the Cause Analysis System for CPCS(CASCPCS) has been developed using the rule-base deduction method to aid the operators in Nuclear Power Plant

  14. A Stock Trading Recommender System Based on Temporal Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Binoy B. Nair

    2015-04-01

    Full Text Available Recommender systems capable of discovering patterns in stock price movements and generating stock recommendations based on the patterns thus discovered can significantly supplement the decision-making process of a stock trader. Such recommender systems are of great significance to a layperson who wishes to profit by stock trading even while not possessing the skill or expertise of a seasoned trader. A genetic algorithm optimized Symbolic Aggregate approXimation (SAX–Apriori based stock trading recommender system, which can mine temporal association rules from the stock price data set to generate stock trading recommendations, is presented in this article. The proposed system is validated on 12 different data sets. The results indicate that the proposed system significantly outperforms the passive buy-and-hold strategy, offering scope for a layperson to successfully invest in capital markets.

  15. Optical MSD symbolic substitution system based on a higher ordered rule

    Science.gov (United States)

    Reddy, A. K.; Mallikarjun, Tatipamula; Raina, J. P.

    1992-12-01

    The advantages provided by Photonic Computing has been well documented. An Optical arithmetic processor has to take full advantage of the massive parallelism in optical signals. Such a processor, using the Modified - Signed - Digit (MSD) number . (i) representation, has been presented here based (2) on the symbolic substitution 1ogi. The higher order symbolic substitution rules are formulated for the addition operation, which is carried out in just two steps. Based on the addition operation, the other arithmetic operations - subtraction, multiplication and division - are implemented. Finally, the usefulness of this MSD system is studied.

  16. Prioritized rule based load management technique for residential building powered by PV/battery system

    Directory of Open Access Journals (Sweden)

    T.R. Ayodele

    2017-06-01

    Full Text Available In recent years, Solar Photovoltaic (PV system has presented itself as one of the main solutions to the electricity poverty plaguing the majority of buildings in rural communities with solar energy potential. However, the stochasticity associated with solar PV power output owing to vagaries in weather conditions is a major challenge in the deployment of the systems. This study investigates approach for maximizing the benefits of a Stand-Alone Photovoltaic-Battery (SAPVB system via techniques that provide for optimum energy gleaning and management. A rule-based load management scheme is developed and tested for a residential building. The approach allows load prioritizing and shifting based on certain rules. To achieve this, the residential loads are classified into Critical Loads (CLs and Uncritical Loads (ULs. The CLs are given higher priority and therefore are allowed to operate at their scheduled time while the ULs are of less priority, hence can be shifted to a time where there is enough electric power generation from the PV arrays rather than the loads being operated at the time period set by the user. Four scenarios were created to give insight into the applicability of the proposed rule based load management scheme. The result revealed that when the load management technique is not utilized as in the case of scenario 1 (Base case, the percentage satisfaction of the critical and uncritical loads by the PV system are 49.8% and 23.7%. However with the implementation of the load management scheme in scenarios 2, 3 and 4, the percentage satisfaction of the loads (CLs, ULs are (93.8%, 74.2%, (90.9%, 70.1% and (87.2%, 65.4% for scenarios 2, 3 and 4, respectively.

  17. A rule-based expert system for generating control displays at the Advanced Photon Source

    International Nuclear Information System (INIS)

    Coulter, K.J.

    1993-01-01

    The integration of a rule-based expert system for generating screen displays for controlling and monitoring instrumentation under the Experimental Physics and Industrial Control System (EPICS) is presented. The expert system is implemented using CLIPS, an expert system shell from the Software Technology Branch at Lyndon B. Johnson Space Center. The user selects the hardware input and output to be displayed and the expert system constructs a graphical control screen appropriate for the data. Such a system provides a method for implementing a common look and feel for displays created by several different users and reduces the amount of time required to create displays for new hardware configurations. Users are able to modify the displays as needed using the EPICS display editor tool

  18. A rule-based expert system for generating control displays at the advanced photon source

    International Nuclear Information System (INIS)

    Coulter, K.J.

    1994-01-01

    The integration of a rule-based expert system for generating screen displays for controlling and monitoring instrumentation under the Experimental Physics and Industrial Control System (EPICS) is presented. The expert system is implemented using CLIPS, an expert system shell from the Software Technology Branch at Lyndon B. Johnson Space Center. The user selects the hardware input and output to be displayed and the expert system constructs a graphical control screen appropriate for the data. Such a system provides a method for implementing a common look and feel for displays created by several different users and reduces the amount of time required to create displays for new hardware configurations. Users are able to modify the displays as needed using the EPICS display editor tool. ((orig.))

  19. Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

    Science.gov (United States)

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

    Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.

  20. Multi-arrhythmias detection with an XML rule-based system from 12-Lead Electrocardiogram.

    Science.gov (United States)

    Khelassi, Abdeldjalil; Yelles-Chaouche, Sarra-Nassira; Benais, Faiza

    2017-05-01

    The computer-aided detection of cardiac arrhythmias stills a crucial application in medical technologies. The rule based systems RBS ensure a high level of transparency and interpretability of the obtained results. To facilitate the diagnosis of the cardiologists and to reduce the uncertainty made in this diagnosis. In this research article, we have realized a classification and automatic recognition of cardiac arrhythmias, by using XML rules that represent the cardiologist knowledge. Thirteen experiments with different knowledge bases were realized for improving the performance of the used method in the detection of 13 cardiac arrhythmias. In the first 12 experiments, we have designed a specialized knowledge base for each cardiac arrhythmia, which contains just one arrhythmia detection rule. In the last experiment, we applied the knowledge base which contains rules of 12 arrhythmias. We used, for the experiments, an international data set with 279 features and 452 records characterizing 12 leads of ECG signal and social information of patients. The data sets were constructed and published at Bilkent University of Ankara, Turkey. In addition, the second version of the self-developed software "XMLRULE" was used; the software can infer more than one class and facilitate the interpretability of the obtained results. The 12 first experiments give 82.80% of correct detection as the mean of all experiments, the results were between 19% and 100% with a low rate in just one experiment. The last experiment in which all arrhythmias are considered, the results of correct detection was 38.33% with 90.55% of sensibility and 46.24% of specificity. It was clearly show that in these results the good choice of the classification model is very beneficial in terms of performance. The obtained results were better than the published results with other computational methods for the mono class detection, but it was less in multi-class detection. The RBS is the most transparent method for

  1. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    Science.gov (United States)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  2. Improving the anesthetic process by a fuzzy rule based medical decision system.

    Science.gov (United States)

    Mendez, Juan Albino; Leon, Ana; Marrero, Ayoze; Gonzalez-Cava, Jose M; Reboso, Jose Antonio; Estevez, Jose Ignacio; Gomez-Gonzalez, José F

    2018-01-01

    The main objective of this research is the design and implementation of a new fuzzy logic tool for automatic drug delivery in patients undergoing general anesthesia. The aim is to adjust the drug dose to the real patient needs using heuristic knowledge provided by clinicians. A two-level computer decision system is proposed. The idea is to release the clinician from routine tasks so that he can focus on other variables of the patient. The controller uses the Bispectral Index (BIS) to assess the hypnotic state of the patient. Fuzzy controller was included in a closed-loop system to reach the BIS target and reject disturbances. BIS was measured using a BIS VISTA monitor, a device capable of calculating the hypnosis level of the patient through EEG information. An infusion pump with propofol 1% is used to supply the drug to the patient. The inputs to the fuzzy inference system are BIS error and BIS rate. The output is infusion rate increment. The mapping of the input information and the appropriate output is given by a rule-base based on knowledge of clinicians. To evaluate the performance of the fuzzy closed-loop system proposed, an observational study was carried out. Eighty one patients scheduled for ambulatory surgery were randomly distributed in 2 groups: one group using a fuzzy logic based closed-loop system (FCL) to automate the administration of propofol (42 cases); the second group using manual delivering of the drug (39 cases). In both groups, the BIS target was 50. The FCL, designed with intuitive logic rules based on the clinician experience, performed satisfactorily and outperformed the manual administration in patients in terms of accuracy through the maintenance stage. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. WINE ADVISOR EXPERT SYSTEM USING DECISION RULES

    Directory of Open Access Journals (Sweden)

    Dinuca Elena Claudia

    2013-07-01

    Full Text Available In this article I focus on developing an expert system for advising the choice of wine that best matches a specific occasion. An expert system is a computer application that performs a task that would be performed by a human expert. The implementation is done using Delphi programming language. I used to represent the knowledge bases a set of rules. The rules are of type IF THEN ELSE rules, decision rules based on different important wine features.

  4. Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

    Science.gov (United States)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2013-04-01

    Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total

  5. A new methodology for the study of FAC phenomenon based on a fuzzy rule system

    International Nuclear Information System (INIS)

    Ferreira Guimaraes, Antonio Cesar

    2003-01-01

    This work consists of the representation of the corrosion problem, FAC - 'Flow-Accelerated Corrosion' in components, structures and passive systems in a nuclear power plant with aging, through a fuzzy rules system, in substitution to the conventional modeling and experimental analyses. Using data characteristic of the nature of the problem to be analyzed, a reduced number of rules can be establish to represent the actual problem. The results can be visualized in a very satisfactory way thus providing the engineer with the knowledge to work in the space of solution of rules to do the necessary inferences

  6. Real-time Geographic Information System (GIS) for Monitoring the Area of Potential Water Level Using Rule Based System

    Science.gov (United States)

    Anugrah, Wirdah; Suryono; Suseno, Jatmiko Endro

    2018-02-01

    Management of water resources based on Geographic Information System can provide substantial benefits to water availability settings. Monitoring the potential water level is needed in the development sector, agriculture, energy and others. In this research is developed water resource information system using real-time Geographic Information System concept for monitoring the potential water level of web based area by applying rule based system method. GIS consists of hardware, software, and database. Based on the web-based GIS architecture, this study uses a set of computer that are connected to the network, run on the Apache web server and PHP programming language using MySQL database. The Ultrasound Wireless Sensor System is used as a water level data input. It also includes time and geographic location information. This GIS maps the five sensor locations. GIS is processed through a rule based system to determine the level of potential water level of the area. Water level monitoring information result can be displayed on thematic maps by overlaying more than one layer, and also generating information in the form of tables from the database, as well as graphs are based on the timing of events and the water level values.

  7. Omega version 2.2: Rule-based deterioration identification and management system. Final report

    International Nuclear Information System (INIS)

    Kataoka, S.; Kojima, T.; Pavinich, W.A.; Andrews, J.D.

    1996-06-01

    This report presents the Omega Version 2.2 (Ωs) rule-based computer program for identifying material deteriorations in the metallic structures, systems and components of LWR nuclear power units. The basis of Us is that understanding what material deteriorations might occur as a function of service life is fundamental to: (1) the development and optimization of preventive maintenance programs, (2) ensuring that current maintenance programs recognize applicable degradations, and (3) demonstrating the adequacy of deterioration management to safety regulatory authorities. The system was developed to assist utility engineers in determining which aging degradation mechanisms are acting on specific components. Direction is also provided to extend this system to manage deterioration and evaluate the efficacy of existing age-related degradation mitigation programs. This system can provide support for justification for continued operation and license renewal. It provides traceability to the data sources used in the logic development. A tiered approach is used to quickly isolate potential age-related degradation for components in a particular location. A potential degradation mechanism is then screened by additional rules to establish its plausibility. Ωs includes a user-friendly system interface and provides default environmental data and materials in the event they are unknown to the user. Ωs produces a report, with references, that validates the elimination of a degradation mechanism from further consideration or the determination that a specific degradation mechanism is acting on a specific material. This report also describes logic for identifying deterioration caused by intrusions and inspection-based deteriorations, along with future plans to program and integrate these features with Ωs

  8. A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler.

    Science.gov (United States)

    Butt, Muhammad Arif; Akram, Muhammad

    2016-01-01

    We present a new intuitionistic fuzzy rule-based decision-making system based on intuitionistic fuzzy sets for a process scheduler of a batch operating system. Our proposed intuitionistic fuzzy scheduling algorithm, inputs the nice value and burst time of all available processes in the ready queue, intuitionistically fuzzify the input values, triggers appropriate rules of our intuitionistic fuzzy inference engine and finally calculates the dynamic priority (dp) of all the processes in the ready queue. Once the dp of every process is calculated the ready queue is sorted in decreasing order of dp of every process. The process with maximum dp value is sent to the central processing unit for execution. Finally, we show complete working of our algorithm on two different data sets and give comparisons with some standard non-preemptive process schedulers.

  9. Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling.

    Science.gov (United States)

    Chavali, Arvind K; Gianchandani, Erwin P; Tung, Kenneth S; Lawrence, Michael B; Peirce, Shayn M; Papin, Jason A

    2008-12-01

    The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.

  10. Oil palm fresh fruit bunch ripeness classification based on rule- based expert system of ROI image processing technique results

    International Nuclear Information System (INIS)

    Alfatni, M S M; Shariff, A R M; Marhaban, M H; Shafie, S B; Saaed, O M B; Abdullah, M Z; BAmiruddin, M D

    2014-01-01

    There is a processing need for a fast, easy and accurate classification system for oil palm fruit ripeness. Such a system will be invaluable to farmers and plantation managers who need to sell their oil palm fresh fruit bunch (FFB) for the mill as this will avoid disputes. In this paper,a new approach was developed under the name of expert rules-based systembased on the image processing techniques results of thethree different oil palm FFB region of interests (ROIs), namely; ROI1 (300x300 pixels), ROI2 (50x50 pixels) and ROI3 (100x100 pixels). The results show that the best rule-based ROIs for statistical colour feature extraction with k-nearest neighbors (KNN) classifier at 94% were chosen as well as the ROIs that indicated results higher than the rule-based outcome, such as the ROIs of statistical colour feature extraction with artificial neural network (ANN) classifier at 94%, were selected for further FFB ripeness inspection system

  11. Optimizing human-system interface automation design based on a skill-rule-knowledge framework

    International Nuclear Information System (INIS)

    Lin, Chiuhsiang Joe; Yenn, T.-C.; Yang, C.-W.

    2010-01-01

    This study considers the technological change that has occurred in complex systems within the past 30 years. The role of human operators in controlling and interacting with complex systems following the technological change was also investigated. Modernization of instrumentation and control systems and components leads to a new issue of human-automation interaction, in which human operational performance must be considered in automated systems. The human-automation interaction can differ in its types and levels. A system design issue is usually realized: given these technical capabilities, which system functions should be automated and to what extent? A good automation design can be achieved by making an appropriate human-automation function allocation. To our knowledge, only a few studies have been published on how to achieve appropriate automation design with a systematic procedure. Further, there is a surprising lack of information on examining and validating the influences of levels of automation (LOAs) on instrumentation and control systems in the advanced control room (ACR). The study we present in this paper proposed a systematic framework to help in making an appropriate decision towards types of automation (TOA) and LOAs based on a 'Skill-Rule-Knowledge' (SRK) model. From the evaluating results, it was shown that the use of either automatic mode or semiautomatic mode is insufficient to prevent human errors. For preventing the occurrences of human errors and ensuring the safety in ACR, the proposed framework can be valuable for making decisions in human-automation allocation.

  12. Rule Based Expert System for Monitoring Real Time Drug Supply in Hospital Using Radio Frequency Identification Technology

    Science.gov (United States)

    Driandanu, Galih; Surarso, Bayu; Suryono

    2018-02-01

    A radio frequency identification (RFID) has obtained increasing attention with the emergence of various applications. This study aims to examine the implementation of rule based expert system supported by RFID technology into a monitoring information system of drug supply in a hospital. This research facilitates in monitoring the real time drug supply by using data sample from the hospital pharmacy. This system able to identify and count the number of drug and provide warning and report in real time. the conclusion is the rule based expert system and RFID technology can facilitate the performance in monitoring the drug supply quickly and precisely.

  13. RFID sensor-tags feeding a context-aware rule-based healthcare monitoring system.

    Science.gov (United States)

    Catarinucci, Luca; Colella, Riccardo; Esposito, Alessandra; Tarricone, Luciano; Zappatore, Marco

    2012-12-01

    Along with the growing of the aging population and the necessity of efficient wellness systems, there is a mounting demand for new technological solutions able to support remote and proactive healthcare. An answer to this need could be provided by the joint use of the emerging Radio Frequency Identification (RFID) technologies and advanced software choices. This paper presents a proposal for a context-aware infrastructure for ubiquitous and pervasive monitoring of heterogeneous healthcare-related scenarios, fed by RFID-based wireless sensors nodes. The software framework is based on a general purpose architecture exploiting three key implementation choices: ontology representation, multi-agent paradigm and rule-based logic. From the hardware point of view, the sensing and gathering of context-data is demanded to a new Enhanced RFID Sensor-Tag. This new device, de facto, makes possible the easy integration between RFID and generic sensors, guaranteeing flexibility and preserving the benefits in terms of simplicity of use and low cost of UHF RFID technology. The system is very efficient and versatile and its customization to new scenarios requires a very reduced effort, substantially limited to the update/extension of the ontology codification. Its effectiveness is demonstrated by reporting both customization effort and performance results obtained from validation in two different healthcare monitoring contexts.

  14. Ontology-based concept map learning path reasoning system using SWRL rules

    Energy Technology Data Exchange (ETDEWEB)

    Chu, K.-K.; Lee, C.-I. [National Univ. of Tainan, Taiwan (China). Dept. of Computer Science and Information Learning Technology

    2010-08-13

    Concept maps are graphical representations of knowledge. Concept mapping may reduce students' cognitive load and extend simple memory function. The purpose of this study was on the diagnosis of students' concept map learning abilities and the provision of personally constructive advice dependant on their learning path and progress. Ontology is a useful method with which to represent and store concept map information. Semantic web rule language (SWRL) rules are easy to understand and to use as specific reasoning services. This paper discussed the selection of grade 7 lakes and rivers curriculum for which to devise a concept map learning path reasoning service. The paper defined a concept map e-learning ontology and two SWRL semantic rules, and collected users' concept map learning path data to infer implicit knowledge and to recommend the next learning path for users. It was concluded that the designs devised in this study were feasible and advanced and the ontology kept the domain knowledge preserved. SWRL rules identified an abstraction model for inferred properties. Since they were separate systems, they did not interfere with each other, while ontology or SWRL rules were maintained, ensuring persistent system extensibility and robustness. 15 refs., 1 tab., 8 figs.

  15. A study on development of a rule based expert system for steam generator life extension

    International Nuclear Information System (INIS)

    Park, Jin Kyun

    1994-02-01

    The need of predicting the integrity of the steam generator(SG) tubes and environmental conditions that affect their integrity is growing to secure nuclear power plant(NPP) safety and enhance plant availability. To achieve their objectives it is important to diagnose the integrity of the SG tubes. An expert system called FEMODES(failure mode diagnosis expert system) has been developed for diagnosis of such tube degradation phenomena as denting, intergranular attack(IGA) and stress corrosion cracking(SCC) in the secondary side of the SG. It is possible with use of FEMODES to estimate possibilities of SG tube degradation and diagnosis environmental conditions that influence such tube degradation. The method of certainty factor theory(CFT) and the rule based backward reasoning inference strategy are used to develop FEMODES. The information required for diagnosis is acquired from SG tube degradation experiences of two local reference plants, some limited oversea plants and technical reports/research papers about such tube degradation. Overall results estimated with use of FEMODES are in reasonable agreement with actual SG tube degradation. Some discrepancy observed in several estimated values of SG tube degradation appears to be due to insufficient heuristic knowledge for knowledge data base of FEMODES

  16. Fuzzylot: a novel self-organising fuzzy-neural rule-based pilot system for automated vehicles.

    Science.gov (United States)

    Pasquier, M; Quek, C; Toh, M

    2001-10-01

    This paper presents part of our research work concerned with the realisation of an Intelligent Vehicle and the technologies required for its routing, navigation, and control. An automated driver prototype has been developed using a self-organising fuzzy rule-based system (POPFNN-CRI(S)) to model and subsequently emulate human driving expertise. The ability of fuzzy logic to represent vague information using linguistic variables makes it a powerful tool to develop rule-based control systems when an exact working model is not available, as is the case of any vehicle-driving task. Designing a fuzzy system, however, is a complex endeavour, due to the need to define the variables and their associated fuzzy sets, and determine a suitable rule base. Many efforts have thus been devoted to automating this process, yielding the development of learning and optimisation techniques. One of them is the family of POP-FNNs, or Pseudo-Outer Product Fuzzy Neural Networks (TVR, AARS(S), AARS(NS), CRI, Yager). These generic self-organising neural networks developed at the Intelligent Systems Laboratory (ISL/NTU) are based on formal fuzzy mathematical theory and are able to objectively extract a fuzzy rule base from training data. In this application, a driving simulator has been developed, that integrates a detailed model of the car dynamics, complete with engine characteristics and environmental parameters, and an OpenGL-based 3D-simulation interface coupled with driving wheel and accelerator/ brake pedals. The simulator has been used on various road scenarios to record from a human pilot driving data consisting of steering and speed control actions associated to road features. Specifically, the POPFNN-CRI(S) system is used to cluster the data and extract a fuzzy rule base modelling the human driving behaviour. Finally, the effectiveness of the generated rule base has been validated using the simulator in autopilot mode.

  17. Ensemble Classifiers for Predicting HIV-1 Resistance from Three Rule-Based Genotypic Resistance Interpretation Systems.

    Science.gov (United States)

    Raposo, Letícia M; Nobre, Flavio F

    2017-08-30

    Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.

  18. Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks

    Directory of Open Access Journals (Sweden)

    Y.-M. Chiang

    2011-01-01

    Full Text Available Pumping stations play an important role in flood mitigation in metropolitan areas. The existing sewerage systems, however, are facing a great challenge of fast rising peak flow resulting from urbanization and climate change. It is imperative to construct an efficient and accurate operating prediction model for pumping stations to simulate the drainage mechanism for discharging the rainwater in advance. In this study, we propose two rule-based fuzzy neural networks, adaptive neuro-fuzzy inference system (ANFIS and counterpropagation fuzzy neural network for on-line predicting of the number of open and closed pumps of a pivotal pumping station in Taipei city up to a lead time of 20 min. The performance of ANFIS outperforms that of CFNN in terms of model efficiency, accuracy, and correctness. Furthermore, the results not only show the predictive water levels do contribute to the successfully operating pumping stations but also demonstrate the applicability and reliability of ANFIS in automatically controlling the urban sewerage systems.

  19. Cracking chaos-based encryption systems ruled by nonlinear time delay differential equations

    International Nuclear Information System (INIS)

    Udaltsov, Vladimir S.; Goedgebuer, Jean-Pierre; Larger, Laurent; Cuenot, Jean-Baptiste; Levy, Pascal; Rhodes, William T.

    2003-01-01

    We report that signal encoding with high-dimensional chaos produced by delayed feedback systems with a strong nonlinearity can be broken. We describe the procedure and illustrate the method with chaotic waveforms obtained from a strongly nonlinear optical system that we used previously to demonstrate signal encryption/decryption with chaos in wavelength. The method can be extended to any systems ruled by nonlinear time-delayed differential equations

  20. A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

    Science.gov (United States)

    Kautzmann, Frank N., III

    1988-01-01

    Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

  1. Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology

    Science.gov (United States)

    Yan, Xinping; Xu, Xiaojian; Sheng, Chenxing; Yuan, Chengqing; Li, Zhixiong

    2018-01-01

    Wear faults are among the chief causes of main-engine damage, significantly influencing the secure and economical operation of ships. It is difficult for engineers to utilize multi-source information to identify wear modes, so an intelligent wear mode identification model needs to be developed to assist engineers in diagnosing wear faults in diesel engines. For this purpose, a multi-level belief rule base (BBRB) system is proposed in this paper. The BBRB system consists of two-level belief rule bases, and the 2D and 3D characteristics of wear particles are used as antecedent attributes on each level. Quantitative and qualitative wear information with uncertainties can be processed simultaneously by the BBRB system. In order to enhance the efficiency of the BBRB, the silhouette value is adopted to determine referential points and the fuzzy c-means clustering algorithm is used to transform input wear information into belief degrees. In addition, the initial parameters of the BBRB system are constructed on the basis of expert-domain knowledge and then optimized by the genetic algorithm to ensure the robustness of the system. To verify the validity of the BBRB system, experimental data acquired from real-world diesel engines are analyzed. Five-fold cross-validation is conducted on the experimental data and the BBRB is compared with the other four models in the cross-validation. In addition, a verification dataset containing different wear particles is used to highlight the effectiveness of the BBRB system in wear mode identification. The verification results demonstrate that the proposed BBRB is effective and efficient for wear mode identification with better performance and stability than competing systems.

  2. Assessing the operation rules of a reservoir system based on a detailed modelling-chain

    Science.gov (United States)

    Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B.

    2014-09-01

    According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two muti-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking, to control floods, to produce hydropower and to reduce low-flow condition. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

  3. Assessing the operation rules of a reservoir system based on a detailed modelling chain

    Science.gov (United States)

    Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B. J.

    2015-03-01

    According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two multi-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking water, to control floods, to produce hydropower and to reduce low-flow conditions. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

  4. Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

    Science.gov (United States)

    Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

    2018-06-01

    Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

    Directory of Open Access Journals (Sweden)

    Jure Demšar

    Full Text Available Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging, group decision-making process, and group behaviour types. The question 'why,' however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

  6. Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden

    International Nuclear Information System (INIS)

    Zhang, Yang; Lundblad, Anders; Campana, Pietro Elia; Benavente, F.; Yan, Jinyue

    2017-01-01

    Highlights: • Battery sizing and rule-based operation are achieved concurrently. • Hybrid operation strategy that combines different strategies is proposed. • Three operation strategies are compared through multi-objective optimization. • High Net Present Value and Self Sufficiency Ratio are achieved at the same time. - Abstract: The optimal components design for grid-connected photovoltaic-battery systems should be determined with consideration of system operation. This study proposes a method to simultaneously optimize the battery capacity and rule-based operation strategy. The investigated photovoltaic-battery system is modeled using single diode photovoltaic model and Improved Shepherd battery model. Three rule-based operation strategies—including the conventional operation strategy, the dynamic price load shifting strategy, and the hybrid operation strategy—are designed and evaluated. The rule-based operation strategies introduce different operation parameters to run the system operation. multi-objective Genetic Algorithm is employed to optimize the decisional variables, including battery capacity and operation parameters, towards maximizing the system’s Self Sufficiency Ratio and Net Present Value. The results indicate that employing battery with the conventional operation strategy is not profitable, although it increases Self Sufficiency Ratio. The dynamic price load shifting strategy has similar performance with the conventional operation strategy because the electricity price variation is not large enough. The proposed hybrid operation strategy outperforms other investigated strategies. When the battery capacity is lower than 72 kW h, Self Sufficiency Ratio and Net Present Value increase simultaneously with the battery capacity.

  7. Development of a cause analysis system for a CPCS trip by using the rule-base deduction method.

    Science.gov (United States)

    Park, Je-Yun; Koo, In-Soo; Sohn, Chang-Ho; Kim, Jung-Seon; Cho, Gi-Ho; Park, Hee-Seok

    2009-07-01

    A Core Protection Calculator System (CPCS) was developed to initiate a Reactor Trip under the circumstance of certain transients by a Combustion Engineering Company. The major function of the Core Protection Calculator System is to generate contact outputs for the Departure from Nucleate Boiling Ratio (DNBR) Trip and a Local Power Density (LPD) Trip. But in a Core Protection Calculator System, a trip cause cannot be identified, thus only trip signals are transferred to the Plant Protection System (PPS) and only the trip status is displayed. It could take a considerable amount of time and effort for a plant operator to analyze the trip causes of a Core Protection Calculator System. So, a Cause Analysis System for a Core Protection Calculator System (CASCPCS) has been developed by using the rule-base deduction method to assist operators in a Nuclear Power Plant. CASCPCS consists of three major parts. Inference engine has a role of controlling the searching knowledge base, executing the rules and tracking the inference process by using the depth-first searching method. Knowledge base consists of four major parts: rules, data base constants, trip buffer variables and causes. And a user interface is implemented by using menu-driven and window display techniques. The advantage of CASCPCS is that it saves time and effort to diagnose the trip causes of a Core Protection Calculator System, it increases a plant's availability and reliability, and it makes it easy to manage CASCPCS because of using only a cursor control.

  8. Model-based Systems Engineering: Creation and Implementation of Model Validation Rules for MOS 2.0

    Science.gov (United States)

    Schmidt, Conrad K.

    2013-01-01

    Model-based Systems Engineering (MBSE) is an emerging modeling application that is used to enhance the system development process. MBSE allows for the centralization of project and system information that would otherwise be stored in extraneous locations, yielding better communication, expedited document generation and increased knowledge capture. Based on MBSE concepts and the employment of the Systems Modeling Language (SysML), extremely large and complex systems can be modeled from conceptual design through all system lifecycles. The Operations Revitalization Initiative (OpsRev) seeks to leverage MBSE to modernize the aging Advanced Multi-Mission Operations Systems (AMMOS) into the Mission Operations System 2.0 (MOS 2.0). The MOS 2.0 will be delivered in a series of conceptual and design models and documents built using the modeling tool MagicDraw. To ensure model completeness and cohesiveness, it is imperative that the MOS 2.0 models adhere to the specifications, patterns and profiles of the Mission Service Architecture Framework, thus leading to the use of validation rules. This paper outlines the process by which validation rules are identified, designed, implemented and tested. Ultimately, these rules provide the ability to maintain model correctness and synchronization in a simple, quick and effective manner, thus allowing the continuation of project and system progress.

  9. The spatial decision-supporting system combination of RBR & CBR based on artificial neural network and association rules

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

    The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.

  10. Integrated Case Based and Rule Based Reasoning for Decision Support

    OpenAIRE

    Eshete, Azeb Bekele

    2009-01-01

    This project is a continuation of my specialization project which was focused on studying theoretical concepts related to case based reasoning method, rule based reasoning method and integration of them. The integration of rule-based and case-based reasoning methods has shown a substantial improvement with regards to performance over the individual methods. Verdande Technology As wants to try integrating the rule based reasoning method with an existing case based system. This project focu...

  11. Horizontal and Vertical Rule Bases Method in Fuzzy Controllers

    OpenAIRE

    Aminifar, Sadegh; bin Marzuki, Arjuna

    2013-01-01

    Concept of horizontal and vertical rule bases is introduced. Using this method enables the designers to look for main behaviors of system and describes them with greater approximations. The rules which describe the system in first stage are called horizontal rule base. In the second stage, the designer modulates the obtained surface by describing needed changes on first surface for handling real behaviors of system. The rules used in the second stage are called vertical rule base. Horizontal...

  12. Comparing a rule based vs. statistical system for automatic categorization of MEDLINE documents according to biomedical specialty

    OpenAIRE

    Humphrey, Susanne M.; Névéol, Aurélie; Browne, Allen; Gobeill, Julien; Ruch, Patrick; Darmoni, Stéfan J.

    2010-01-01

    Automatic document categorization is an important research problem in Information Science and Natural Language Processing. Many applications, including Word Sense Disambiguation and Information Retrieval in large collections, can benefit from such categorization. This paper focuses on automatic categorization of documents from the biomedical literature into broad discipline-based categories. Two different systems are described and contrasted: CISMeF, which uses rules based on human indexing o...

  13. Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems

    Directory of Open Access Journals (Sweden)

    F.

    2012-04-01

    Full Text Available In this paper we propose a new approach for laser-based environment device control systems based on the automatic design of a Fuzzy Rule-Based System for laser pointer detection. The idea is to improve the success rate of the previous approaches decreasing as much as possible the false offs and increasing the success rate in images with laser spot, i.e., the detection of a false laser spot (since this could lead to dangerous situations. To this end, we propose to analyze both, the morphology and color of a laser spot image together, thus developing a new robust algorithm. Genetic Fuzzy Systems have also been employed to improve the laser spot system detection by means of a fine tuning of the involved membership functions thus reducing the system false offs, which is the main objective in this problem. The system presented in this paper, makes use of a Fuzzy Rule-Based System adjusted by a Genetic Algorithm, which, based on laser morphology and color analysis, shows a better success rate than previous approaches.

  14. Experiments in Knowledge Refinement for a Large Rule-Based System

    Science.gov (United States)

    1993-08-01

    empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system

  15. Knowledge base rule partitioning design for CLIPS

    Science.gov (United States)

    Mainardi, Joseph D.; Szatkowski, G. P.

    1990-01-01

    This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

  16. A rule-based expert system for control rod pattern of boiling water reactors by hovering around haling exposure shape

    International Nuclear Information System (INIS)

    Kao, P.-W.; Lin, L.-S.; Yang, J.-T.

    2004-01-01

    Feasible strategies for automatic BWR control rod pattern generation have been implemented in a rule-based expert system. These strategies are majorly based on a concept for which exposure distributions are hovering around the Haling exposure distribution through a cycle while radial and axial power distributions are dominantly controlled by some abstracted factors indicating the desired distributions. The system can either automatically generate expert-level control rod patterns or search for criteria-satisfied patterns originated from user's input. It has successfully been demonstrated by generating control rod patterns for the the 1775 MWth Chinshan plant in Unit I Cycle 13 alternate loading pattern and Unit 2 Cycle 8 but with longer cycle length. All rod patterns for two cycles result in all-rod-out at EOC and no violation against the four criteria. The demonstrations show that the system is considerably good in choosing initial trial rod patterns and adjusting rod patterns to satisfy the design criteria. (author)

  17. Dynamic Programming Approach for Construction of Association Rule Systems

    KAUST Repository

    Alsolami, Fawaz

    2016-11-18

    In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.

  18. Dynamic Programming Approach for Construction of Association Rule Systems

    KAUST Repository

    Alsolami, Fawaz; Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2016-01-01

    In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.

  19. A Web Based Sweet Orange Crop Expert System using Rule Based System and Artificial Bee Colony Optimization Algorithm

    OpenAIRE

    Prof.M.S.Prasad Babu,; Mrs.J.Anitha,; K.Hari Krishna

    2010-01-01

    Citrus fruits have a prominent place among popular and exclusively grown tropical and sub-tropical fruits. Their nature ,multifold nutritional and medicinal values have made them so important. Sweet Orange Crop expert advisory system is aimed at a collaborative venture with eminent Agriculture Scientist and Experts in the area of Sweet Orange Plantation with an excellent team of computer Engineers, Programmers and designers. This Expert System contains two main parts one is Sweet Orange Infor...

  20. Personalization of Rule-based Web Services.

    Science.gov (United States)

    Choi, Okkyung; Han, Sang Yong

    2008-04-04

    Nowadays Web users have clearly expressed their wishes to receive personalized services directly. Personalization is the way to tailor services directly to the immediate requirements of the user. However, the current Web Services System does not provide any features supporting this such as consideration of personalization of services and intelligent matchmaking. In this research a flexible, personalized Rule-based Web Services System to address these problems and to enable efficient search, discovery and construction across general Web documents and Semantic Web documents in a Web Services System is proposed. This system utilizes matchmaking among service requesters', service providers' and users' preferences using a Rule-based Search Method, and subsequently ranks search results. A prototype of efficient Web Services search and construction for the suggested system is developed based on the current work.

  1. An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System.

    Science.gov (United States)

    1982-08-01

    peolea with the se e S knowlede base by observing en t om. W0hile thorough testing is an "samt4 Pert of V*flfyL the ooIlst4ftl and capleteness of a...physicians at Stanford’s Oncology Day Care Center on the management of patients who are on experimental treatment protocols. These protocols serve to...for oncology protocol management . Prooceedings of 7th IJCAI, pp. 876- 881, Vancouver, B.C., August 1981. I. van Melle, W. A Domain-Independent system

  2. Methodological approaches based on business rules

    OpenAIRE

    Anca Ioana ANDREESCU; Adina UTA

    2008-01-01

    Business rules and business processes are essential artifacts in defining the requirements of a software system. Business processes capture business behavior, while rules connect processes and thus control processes and business behavior. Traditionally, rules are scattered inside application code. This approach makes it very difficult to change rules and shorten the life cycle of the software system. Because rules change more quickly than the application itself, it is desirable to externalize...

  3. Implementasi Rule Base System dan Fuzzy Logic Artifical Intelligence pada Game Kartu Capsa

    OpenAIRE

    Pangkatodi, Edo; Liliana, Liliana; Budhi, Gregorius Satia

    2016-01-01

    In the era of globalization today, science and technology is developing very fast, particularly in entertainment media, specifically in the gaming world. Today, games are not only used as an entertainment, but also can be used as an alternative in the world of work, education, and even sports. In the world of gaming, artificial intelligence, or AI is a factor that cannot be separated. With the right methods and the specific rules of the AI can walk like a human being doing a job. So it is not...

  4. A noninvasive method for coronary artery diseases diagnosis using a clinically-interpretable fuzzy rule-based system

    Directory of Open Access Journals (Sweden)

    Hamid Reza Marateb

    2015-01-01

    Full Text Available Background: Coronary heart diseases/coronary artery diseases (CHDs/CAD, the most common form of cardiovascular disease (CVD, are a major cause for death and disability in developing/developed countries. CAD risk factors could be detected by physicians to prevent the CAD occurrence in the near future. Invasive coronary angiography, a current diagnosis method, is costly and associated with morbidity and mortality in CAD patients. The aim of this study was to design a computer-based noninvasive CAD diagnosis system with clinically interpretable rules. Materials and Methods: In this study, the Cleveland CAD dataset from the University of California UCI (Irvine was used. The interval-scale variables were discretized, with cut points taken from the literature. A fuzzy rule-based system was then formulated based on a neuro-fuzzy classifier (NFC whose learning procedure was speeded up by the scaled conjugate gradient algorithm. Two feature selection (FS methods, multiple logistic regression (MLR and sequential FS, were used to reduce the required attributes. The performance of the NFC (without/with FS was then assessed in a hold-out validation framework. Further cross-validation was performed on the best classifier. Results: In this dataset, 16 complete attributes along with the binary CHD diagnosis (gold standard for 272 subjects (68% male were analyzed. MLR + NFC showed the best performance. Its overall sensitivity, specificity, accuracy, type I error (α and statistical power were 79%, 89%, 84%, 0.1 and 79%, respectively. The selected features were "age and ST/heart rate slope categories," "exercise-induced angina status," fluoroscopy, and thallium-201 stress scintigraphy results. Conclusion: The proposed method showed "substantial agreement" with the gold standard. This algorithm is thus, a promising tool for screening CAD patients.

  5. A study on the optimal fuel loading pattern design in pressurized water reactor using the artificial neural network and the fuzzy rule based system

    International Nuclear Information System (INIS)

    Kim, Han Gon; Chang, Soon Heung; Lee, Byung

    2004-01-01

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. In this paper, an optimal loading pattern is defined that the local power peaking factor is lower than predetermined value during one cycle and the effective multiplication factor is maximized in order to extract maximum energy. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (author)

  6. A study on the optimal fuel loading pattern design in pressurized water reactor using the artificial neural network and the fuzzy rule based system

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Han Gon; Chang, Soon Heung; Lee, Byung [Department of Nuclear Engineering, Korea Advanced Institute of Science and Technology, Yusong-gu, Taejon (Korea, Republic of)

    2004-07-01

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. In this paper, an optimal loading pattern is defined that the local power peaking factor is lower than predetermined value during one cycle and the effective multiplication factor is maximized in order to extract maximum energy. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (author)

  7. Optimal reliability design for over-actuated systems based on the MIT rule: Application to an octocopter helicopter testbed

    International Nuclear Information System (INIS)

    Chamseddine, Abbas; Theilliol, Didier; Sadeghzadeh, Iman; Zhang, Youmin; Weber, Philippe

    2014-01-01

    This paper addresses the problem of optimal reliability in over-actuated systems. Overloading an actuator decreases its overall lifetime and reduces its average performance over a long time. Therefore, performance and reliability are two conflicting requirements. While appropriate reliability is related to average loads, good performance is related to fast response and sufficient loads generated by actuators. Actuator redundancy allows us to address both performance and reliability at the same time by properly allocating desired loads among redundant actuators. The main contribution of this paper is the on-line optimization of the overall plant reliability according to performance objective using an MIT (Massachusetts Institute of Technology) rule-based method. The effectiveness of the proposed method is illustrated through an experimental application to an octocopter helicopter testbed

  8. A rule-based phase control methodology for a slider-crank wave energy converter power take-off system

    Energy Technology Data Exchange (ETDEWEB)

    Sang, Yuanrui; Karayaka, H. Bora; Yan, Yanjun; Zhang, James Z.; Bogucki, Darek; Yu, Yi-Hsiang

    2017-09-01

    The slider crank is a proven mechanical linkage system with a long history of successful applications, and the slider-crank ocean wave energy converter (WEC) is a type of WEC that converts linear motion into rotation. This paper presents a control algorithm for a slider-crank WEC. In this study, a time-domain hydrodynamic analysis is adopted, and an AC synchronous machine is used in the power take-off system to achieve relatively high system performance. Also, a rule-based phase control strategy is applied to maximize energy extraction, making the system suitable for not only regular sinusoidal waves but also irregular waves. Simulations are carried out under regular sinusoidal wave and synthetically produced irregular wave conditions; performance validations are also presented with high-precision, real ocean wave surface elevation data. The influences of significant wave height, and peak period upon energy extraction of the system are studied. Energy extraction results using the proposed method are compared to those of the passive loading and complex conjugate control strategies; results show that the level of energy extraction is between those of the passive loading and complex conjugate control strategies, and the suboptimal nature of this control strategy is verified.

  9. Idioms-based Business Rule Extraction

    NARCIS (Netherlands)

    R Smit (Rob)

    2011-01-01

    htmlabstractThis thesis studies the extraction of embedded business rules, using the idioms of the used framework to identify them. Embedded business rules exist as source code in the software system and knowledge about them may get lost. Extraction of those business rules could make them accessible

  10. A C++ Class for Rule-Base Objects

    Directory of Open Access Journals (Sweden)

    William J. Grenney

    1992-01-01

    Full Text Available A C++ class, called Tripod, was created as a tool to assist with the development of rule-base decision support systems. The Tripod class contains data structures for the rule-base and member functions for operating on the data. The rule-base is defined by three ASCII files. These files are translated by a preprocessor into a single file that is located when a rule-base object is instantiated. The Tripod class was tested as part of a proto-type decision support system (DSS for winter highway maintenance in the Intermountain West. The DSS is composed of two principal modules: the main program, called the wrapper, and a Tripod rule-base object. The wrapper is a procedural module that interfaces with remote sensors and an external meterological database. The rule-base contains the logic for advising an inexperienced user and for assisting with the decision making process.

  11. Developing a fuzzy rule based cognitive map for total system safety assessment

    International Nuclear Information System (INIS)

    Lemos, Francisco Luiz de; Sullivan, Terry

    2007-01-01

    Total System Performance Assessment, TSPA, for radioactive waste disposal is a multi and interdisciplinary task that is characterized by complex interactions between parameters and processes; lack of data; and ignorance regarding natural processes and conditions. The vagueness in the determination of ranges of values of parameters and identification of interacting processes pose further difficulties to the analysts with regard to the establishment of the relations between processes and parameters. More specifically the vagueness makes uncertainty propagation and sensitivity analysis challenging to analyze. To cope with these difficulties experts often use simplifications and linguistic terms to express their state of knowledge about a certain situation. For example, experts use terms such as 'low pH', 'very unlikely', etc to describe their perception about natural processes or conditions. In this work we propose the use of Fuzzy Cognitive Maps, FCM, for representation of interrelation between processes and parameters as well as to promote a better understanding of the system performance. Fuzzy cognitive maps are suited for the case where the causal relations are not clearly defined and, therefore, can not be represented by crisp values. In other words, instead of representing the quality of the interactions by crisp values, they are assigned degrees of truth. For example, we can assign values to the effect of one process on another such that (+) 1 corresponds to positive, (-) 1 to negative and 0 to neutral effects respectively. In this case the effect of a process A, on a process, B, can be depicted as function of the membership to the fuzzy set 'causal effect' of the cause process to the target one. One of the main advantages of this methodology would be that it allows one to aggregate the linguistic expressions as descriptions of processes. For example, a process can be known to have a 'very strong' positive effect on another one, or using fuzzy sets terminology

  12. Quantization rules for strongly chaotic systems

    International Nuclear Information System (INIS)

    Aurich, R.; Bolte, J.

    1992-09-01

    We discuss the quantization of strongly chaotic systems and apply several quantization rules to a model system given by the unconstrained motion of a particle on a compact surface of constant negative Gaussian curvature. We study the periodic-orbit theory for distinct symmetry classes corresponding to a parity operation which is always present when such a surface has genus two. Recently, several quantization rules based on periodic orbit theory have been introduced. We compare quantizations using the dynamical zeta function Z(s) with the quantization condition cos(π N(E)) = 0, where a periodix-orbit expression for the spectral staircase N(E) is used. A general discussion of the efficiency of periodic-orbit quantization then allows us to compare the different methods. The system dependence of the efficiency, which is determined by the topological entropy τ and the mean level density anti d(E), is emphasized. (orig.)

  13. A Constructivist Approach to Rule Bases

    NARCIS (Netherlands)

    Sileno, G.; Boer, A.; van Engers, T.; Loiseau, S.; Filipe, J.; Duval, B.; van den Herik, J.

    2015-01-01

    The paper presents a set of algorithms for the conversion of rule bases between priority-based and constraint-based representations. Inspired by research in precedential reasoning in law, such algorithms can be used for the analysis of a rule base, and for the study of the impact of the introduction

  14. Analysis of Rules for Islamic Inheritance Law in Indonesia Using Hybrid Rule Based Learning

    Science.gov (United States)

    Khosyi'ah, S.; Irfan, M.; Maylawati, D. S.; Mukhlas, O. S.

    2018-01-01

    Along with the development of human civilization in Indonesia, the changes and reform of Islamic inheritance law so as to conform to the conditions and culture cannot be denied. The distribution of inheritance in Indonesia can be done automatically by storing the rule of Islamic inheritance law in the expert system. In this study, we analyze the knowledge of experts in Islamic inheritance in Indonesia and represent it in the form of rules using rule-based Forward Chaining (FC) and Davis-Putman-Logemann-Loveland (DPLL) algorithms. By hybridizing FC and DPLL algorithms, the rules of Islamic inheritance law in Indonesia are clearly defined and measured. The rules were conceptually validated by some experts in Islamic laws and informatics. The results revealed that generally all rules were ready for use in an expert system.

  15. Consultation system with knowledge representation by decision rules

    Energy Technology Data Exchange (ETDEWEB)

    Senne, E L.F.; Simoni, P O

    1982-04-01

    The use of decision rules in the representation of empirical knowledge supplied by application domain experts is discussed. Based on this representation, a system is described which employs artificial intelligence techniques to yield inferences within a specific domain. Three modules composing the system are described: the acquisition one, that allows the insertion of new rules; the diagnostic one, that uses rules in the inference process; and the explanation one, that exhibits reasons for each system action.

  16. Medicare and Medicaid Programs; CY 2016 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements. Final rule.

    Science.gov (United States)

    2015-11-05

    This final rule will update Home Health Prospective Payment System (HH PPS) rates, including the national, standardized 60-day episode payment rates, the national per-visit rates, and the non-routine medical supply (NRS) conversion factor under the Medicare prospective payment system for home health agencies (HHAs), effective for episodes ending on or after January 1, 2016. As required by the Affordable Care Act, this rule implements the 3rd year of the 4-year phase-in of the rebasing adjustments to the HH PPS payment rates. This rule updates the HH PPS case-mix weights using the most current, complete data available at the time of rulemaking and provides a clarification regarding the use of the "initial encounter'' seventh character applicable to certain ICD-10-CM code categories. This final rule will also finalize reductions to the national, standardized 60-day episode payment rate in CY 2016, CY 2017, and CY 2018 of 0.97 percent in each year to account for estimated case-mix growth unrelated to increases in patient acuity (nominal case-mix growth) between CY 2012 and CY 2014. In addition, this rule implements a HH value-based purchasing (HHVBP) model, beginning January 1, 2016, in which all Medicare-certified HHAs in selected states will be required to participate. Finally, this rule finalizes minor changes to the home health quality reporting program and minor technical regulations text changes.

  17. Rule-based Energy Management System in an Experimental Microgrid with the Presence of Time of Use Tariffs

    Directory of Open Access Journals (Sweden)

    Moghimi Mojtaba

    2016-01-01

    Full Text Available This paper aims to investigate a method of peak load shaving through the utilization of solar PV and battery energy storage whilst creating a cost effective Energy Management System (EMS. This is achieved by utilizing a rule-sets to manage and optimize a scheduling system with a forecasting algorithm. As Time of Use (ToU tariffs change throughout the day, a cost benefit can be achieved when a smart energy storage system is appropriately employed. The EMS operation is tested on an experimental microgrid with commercial load considering payback period calculation.

  18. A Fuzzy Rule-based Controller For Automotive Vehicle Guidance

    OpenAIRE

    Hessburg, Thomas; Tomizuka, Masayoshi

    1991-01-01

    A fuzzy rule-based controller is applied to lateral guidance of a vehicle for an automated highway system. The fuzzy rules, based on human drivers' experiences, are developed to track the center of a lane in the presence of external disturbances and over a range of vehicle operating conditions.

  19. A decision support system and rule-based algorithm to augment the human interpretation of the 12-lead electrocardiogram.

    Science.gov (United States)

    Cairns, Andrew W; Bond, Raymond R; Finlay, Dewar D; Guldenring, Daniel; Badilini, Fabio; Libretti, Guido; Peace, Aaron J; Leslie, Stephen J

    The 12-lead Electrocardiogram (ECG) has been used to detect cardiac abnormalities in the same format for more than 70years. However, due to the complex nature of 12-lead ECG interpretation, there is a significant cognitive workload required from the interpreter. This complexity in ECG interpretation often leads to errors in diagnosis and subsequent treatment. We have previously reported on the development of an ECG interpretation support system designed to augment the human interpretation process. This computerised decision support system has been named 'Interactive Progressive based Interpretation' (IPI). In this study, a decision support algorithm was built into the IPI system to suggest potential diagnoses based on the interpreter's annotations of the 12-lead ECG. We hypothesise semi-automatic interpretation using a digital assistant can be an optimal man-machine model for ECG interpretation. To improve interpretation accuracy and reduce missed co-abnormalities. The Differential Diagnoses Algorithm (DDA) was developed using web technologies where diagnostic ECG criteria are defined in an open storage format, Javascript Object Notation (JSON), which is queried using a rule-based reasoning algorithm to suggest diagnoses. To test our hypothesis, a counterbalanced trial was designed where subjects interpreted ECGs using the conventional approach and using the IPI+DDA approach. A total of 375 interpretations were collected. The IPI+DDA approach was shown to improve diagnostic accuracy by 8.7% (although not statistically significant, p-value=0.1852), the IPI+DDA suggested the correct interpretation more often than the human interpreter in 7/10 cases (varying statistical significance). Human interpretation accuracy increased to 70% when seven suggestions were generated. Although results were not found to be statistically significant, we found; 1) our decision support tool increased the number of correct interpretations, 2) the DDA algorithm suggested the correct

  20. Gaming the system. Dodging the rules, ruling the dodgers.

    Science.gov (United States)

    Morreim, E H

    1991-03-01

    Although traditional obligations of fidelity require physicians to deliver quality care to their patients, including to utilize costly technologies, physicians are steadily losing their accustomed control over the necessary resources. The "economic agents" who own the medical and monetary resources of care now impose a wide array of rules and restrictions in order to contain their costs of operation. However, physicians can still control resources indirectly through "gaming the system," employing tactics such as "fudging" that exploit resource rules' ambiguity and flexibility to bypass the rules while ostensibly honoring them. Physicians may be especially inclined to game the system where resource rules seriously underserve patients' needs, where economic agents seem to be "gaming the patient," with needless obstacles to care, or where others, such as hospitals or even physicians themselves, may be denied needed reimbursements. Though tempting, gaming is morally and medically hazardous. It can harm patients and society, offend honesty, and violate basic principles of contractual and distributive justice. It is also, in fact, usually unnecessary in securing needed resources for patients. More fundamentally, we must reconsider what physicians owe their patients. They owe what is theirs to give: their competence, care and loyalty. In light of medicine's changing economics, two new duties emerge: economic advising, whereby physicians explicitly discuss the economic as well as medical aspects of each treatment option; and economic advocacy, whereby physicians intercede actively on their patients' behalf with the economic agents who control the resources.

  1. Electromagnetic compatibility design and cabling system rules

    International Nuclear Information System (INIS)

    Raimbourg, J.

    2009-01-01

    This report is devoted to establish EMC (Electromagnetic Compatibility) design and cabling system rules. It is intended for hardware designers in charge of designing electronic maps or integrating existing materials into a comprehensive system. It is a practical guide. The rules described in this document do not require enhanced knowledge of advanced mathematical or physical concepts. The key point is to understand phenomena with a pragmatic approach to highlight the design and protection rules. (author)

  2. Rule-based Information Integration

    NARCIS (Netherlands)

    de Keijzer, Ander; van Keulen, Maurice

    2005-01-01

    In this report, we show the process of information integration. We specifically discuss the language used for integration. We show that integration consists of two phases, the schema mapping phase and the data integration phase. We formally define transformation rules, conversion, evolution and

  3. [Analysis on medication rules of modern traditional Chinese medicines in treating palpitations based on traditional Chinese medicine inheritance support system].

    Science.gov (United States)

    Sun, Zhi-Xin; Zhang, Pan-Pan; Gao, Wu-Lin; Dai, Guo-Hua

    2017-01-01

    To analyze the prescription and medication rules of Chinese medicines in the treatment of palpitations in the Chinese journal full text database(CNKI) by using traditional Chinese medicine inheritance system, and provide a reference for further research and development of modern traditional Chinese medicines(TCMs) in treatment of palpitations. In order to give better guidance for clinical mediation, prescriptions used for treatment of palpitations in CNKI were collected, and then were input to the TCM inheritance support system for establishing a Chinese medicine prescription database for palpitations. The software's revised mutual information, complex system entropy clustering and other data mining methods were adopted to analyze the prescriptions according to the frequencies of herbs, "four natures", "five flavors" and "meridians" of the high-frequency medicines in the database, identify the core herbs and application characteristics, and analyze the prescription rules and medication experience. Totally, 545 prescriptions used for palpitation were included in this study and involved 247 Chinese herbs. The analysis results showed that the herbs in prescriptions for palpitation mostly had the warm property, and the herbs in heart and spleen meridian accounted for a larger proportion, indicating that the treatment was mainly to nourish heart and strengthen spleen. The top 11 herbs in usage frequency were consistent with the high-frequency medicines in medication patterns of common herbal pairs; therefore, we considered that these 11 herbs were the core herbs; the core herbal combination included Cassia Twig, Licorice, fossil fragments, Ostreae decoction, and evolved into 9 new prescriptions for treating palpitation. Our results objectively presented the prescription and medication rules for treating palpitation and provided extremely effective guidance for the clinical therapy. Copyright© by the Chinese Pharmaceutical Association.

  4. Horizontal and Vertical Rule Bases Method in Fuzzy Controllers

    Directory of Open Access Journals (Sweden)

    Sadegh Aminifar

    2013-01-01

    Full Text Available Concept of horizontal and vertical rule bases is introduced. Using this method enables the designers to look for main behaviors of system and describes them with greater approximations. The rules which describe the system in first stage are called horizontal rule base. In the second stage, the designer modulates the obtained surface by describing needed changes on first surface for handling real behaviors of system. The rules used in the second stage are called vertical rule base. Horizontal and vertical rule bases method has a great roll in easing of extracting the optimum control surface by using too lesser rules than traditional fuzzy systems. This research involves with control of a system with high nonlinearity and in difficulty to model it with classical methods. As a case study for testing proposed method in real condition, the designed controller is applied to steaming room with uncertain data and variable parameters. A comparison between PID and traditional fuzzy counterpart and our proposed system shows that our proposed system outperforms PID and traditional fuzzy systems in point of view of number of valve switching and better surface following. The evaluations have done both with model simulation and DSP implementation.

  5. Rule of Law. Peculiarities of Kosovo System

    Directory of Open Access Journals (Sweden)

    Iliriana ISLAMI

    2017-03-01

    Full Text Available Nowadays there is a general call, of every international institution, meaning EU, and other international mechanism requiring and basing their policies on the principle of conditionality (Pippan, 2004 by urging states to undertake steps to fulfill the whole range of political and economic conditions in return for partnership, membership or monetary aid. Conditionality is screened through the new lenses of order and stability based on rule of law, democracy, free market economy, and respect for human rights and minority rights, envisaged as Western values. (Copenhagen Criteria, 1993 To achieve this aim the rule of law is considered as occupying a unique position in a democratic society, therefore it is called upon states to create conditions for reforms on a judiciary as the traditional mechanism to decide on disputes, to protect citizens from the arbitrary political affiliation or private individuals. As such, it fights corruption too. (Un Judge Simply said it is required from the states to create conditions to achieve the independent judiciary, through which democratic society can be created. As such, these analyses give hints on the issue of rule of law from the transitional phase of UNMIK to Kosovar Institution elucidating the presence of the EU EULEX Mission, too. Therefore, in the case of Kosovo the challenge of the judiciary system was twofold concerning UNMIK and EU Mission and the establishment of the Kosovo Constitution from another side.

  6. Incremental Learning of Context Free Grammars by Parsing-Based Rule Generation and Rule Set Search

    Science.gov (United States)

    Nakamura, Katsuhiko; Hoshina, Akemi

    This paper discusses recent improvements and extensions in Synapse system for inductive inference of context free grammars (CFGs) from sample strings. Synapse uses incremental learning, rule generation based on bottom-up parsing, and the search for rule sets. The form of production rules in the previous system is extended from Revised Chomsky Normal Form A→βγ to Extended Chomsky Normal Form, which also includes A→B, where each of β and γ is either a terminal or nonterminal symbol. From the result of bottom-up parsing, a rule generation mechanism synthesizes minimum production rules required for parsing positive samples. Instead of inductive CYK algorithm in the previous version of Synapse, the improved version uses a novel rule generation method, called ``bridging,'' which bridges the lacked part of the derivation tree for the positive string. The improved version also employs a novel search strategy, called serial search in addition to minimum rule set search. The synthesis of grammars by the serial search is faster than the minimum set search in most cases. On the other hand, the size of the generated CFGs is generally larger than that by the minimum set search, and the system can find no appropriate grammar for some CFL by the serial search. The paper shows experimental results of incremental learning of several fundamental CFGs and compares the methods of rule generation and search strategies.

  7. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha

    2013-11-25

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  8. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  9. A study on the development of the on-line operator aid system using rule based expert system and fuzzy logic for nuclear power plants

    International Nuclear Information System (INIS)

    Kang, Ki Sig

    1995-02-01

    The on - line Operator Aid SYStem (OASYS) has been developed to support operator's decision making process and to ensure the safety of nuclear power plants (NPPs) by timely providing operators with proper guidelines according to the plant operation mode. The OASYS consists of four systems such as the signal validation and management system (SVMS), the plant monitoring system (PMS), the alarm filtering and diagnostic system (AFDS), and the dynamic emergency procedure tracking system (DEPTS). The SVMS and the PMS help operators to maintain a plant as a normal operation condition. The AFDS covers the abnormal events until they result in exceeding the limit range of reactor trip signals, while after a reactor trip, the DEPTS aids operators with proper guidelines so as to shutdown safely. The OASYS uses a rule based expert system and a fuzzy logic. The rule based expert system is used to classify the pre-defined events and track the emergency operating procedures (EOPs) through data processing. The fuzzy logic is used to generate the conceptual high level alarms for the prognostic diagnosis and to evaluate the qualitative fuzzy criteria used in EOPs. Performance assessment of the OASYS demonstrates that it is capable of diagnosing plant abnormal conditions and providing operators appropriate guidelines with fast response time and consistency. The developed technology for OASYS will be used to design the Integrated Advanced Control Room in which a plant can be operated by one operator during normal operation. The advanced EOP for emergency operation has been developed by focusing attention on the importance of the operators' role in emergency conditions. To overcome the complexity of current EOPs and maintain the consistency of operators' action according to plant emergency conditions, operator's tasks were allocated according to their duties in the advanced EOP and the computerized operator aid system (COAS) has been developed as an alternative to reduce operator

  10. AUTOCAT. Knowledge-based formal acquisition system according to INIS rules demonstrated by the example of physics core journals

    International Nuclear Information System (INIS)

    1986-07-01

    The AUTOCAT system is designed to perform the following two main tasks: - Orientation in the input data representing a given journal, or relevant contents thereof, with the main purpose of the identification process being to yield a task-specific interpretation of all relevant parts of text. - Transformation of the information units found in the input data into the AUTOCAT output format, in accordance with the INIS Cataloguing Rules. Since the processing structure largely depends on the (static) structure of journals, the representation of the object structure of the various physics core journals selected for the project is of great importance. Among the various representation concepts available, frames are particularly suited for use as an underlying data structure. So the frame concept of Minsky will be modified and enhanced to meet the specific requirements of the project. The basic information for data handling. i.e. identification and cataloguing, will be codified to rules and integrated into the frame concept. Realisation is planned to be in PROLOG. (orig./WB) [de

  11. Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules

    Science.gov (United States)

    Hassanpour, Saeed; O'Connor, Martin J.; Das, Amar K.

    Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases increases, developers and end users need methods of rule abstraction to facilitate rule management. In this paper, we describe a rule abstraction method for Semantic Web Rule Language (SWRL) rules that is based on lexical analysis and a set of heuristics. Our method results in a tree data structure that we exploit in creating techniques to visualize, paraphrase, and categorize SWRL rules. We evaluate our approach by applying it to several biomedical ontologies that contain SWRL rules, and show how the results reveal rule patterns within the rule base. We have implemented our method as a plug-in tool for Protégé-OWL, the most widely used ontology modeling software for the Semantic Web. Our tool can allow users to rapidly explore content and patterns in SWRL rule bases, enabling their acquisition and management.

  12. A study on the optimal fuel loading pattern design in pressurized water reactors using the artificial neural network and the fuzzy rule based system

    International Nuclear Information System (INIS)

    Kim, Han Gon

    1993-02-01

    In pressurized water reactors, the fuel reloading problem has significant meaning in terms of both safety and economic aspects. Therefore the general problem of incore fuel management for a PWR consists of determining the fuel reloading policy for each cycle that minimize unit energy cost under the constraints imposed on various core parameters, e.g., a local power peaking factor and an assembly burnup. This is equivalent that a cycle length is maximized for a given energy cost under the various constraints. Existing optimization methods do not ensure the global optimum solution because of the essential limitation of their searching algorithms. They only find near optimal solutions. To solve this limitation, a hybrid artificial neural network system is developed for the optimal fuel loading pattern design using a fuzzy rule based system and an artificial neural networks. This system finds the patterns that P max is lower than the predetermined value and K eff is larger than the reference value. The back-propagation networks are developed to predict PWR core parameters. Reference PWR is an 121-assembly typical PWR. The local power peaking factor and the effective multiplication factor at BOC condition are predicted. To obtain target values of these two parameters, the QCC code are used. Using this code, 1000 training patterns are obtained, randomly. Two networks are constructed, one for P max and another for K eff Both of two networks have 21 input layer neurons, 18 output layer neurons, and 120 and 393 hidden layer neurons, respectively. A new learning algorithm is proposed. This is called the advanced adaptive learning algorithm. The weight change step size of this algorithm is optimally varied inversely proportional to the average difference between an actual output value and an ideal target value. This algorithm greatly enhances the convergence speed of a BPN. In case of P max prediction, 98% of the untrained patterns are predicted within 6% error, and in case

  13. CBP Customs Rulings Online Search System (CROSS)

    Data.gov (United States)

    Department of Homeland Security — CROSS is a searchable database of CBP rulings that can be retrieved based on simple or complex search characteristics using keywords and Boolean operators. CROSS has...

  14. Business rules formalisation for information systems

    Directory of Open Access Journals (Sweden)

    Ivana Rábová

    2010-01-01

    Full Text Available The article deals with relation business rules and business applications and describes a number of structures for support of information systems implementation and customization. Particular formats of structure are different according to different type of business rules. We arise from model of enterprise architecture that is a significant document of all what happens in business and serves for blueprint and facilitates of managers decisions. Most complicated part of enterprise architecture is business rule. When we gain its accurate formulation and when we achieve to formalize and to store business rule in special repository we can manage it actualize it and use it for many reasons. The article emphasizes formats of business rule formalization and its reference to business applications implementation.

  15. Oil drilling rig diesel power-plant fuel efficiency improvement potentials through rule-based generator scheduling and utilization of battery energy storage system

    International Nuclear Information System (INIS)

    Pavković, Danijel; Sedić, Almir; Guzović, Zvonimir

    2016-01-01

    Highlights: • Isolated oil drilling rig microgrid power flows are analyzed over 30 days. • Rule-based diesel generator scheduling is proposed to reduce fuel consumption. • A battery energy storage is parameterized and used for peak load leveling. • The effectiveness of proposed hybrid microgrid is verified by simulations. • Return-of-investment might be expected within 20% of battery system lifetime. - Abstract: This paper presents the development of a rule-based energy management control strategy suitable for isolated diesel power-plants equipped with a battery energy storage system for peak load shaving. The proposed control strategy includes the generator scheduling strategy and peak load leveling scheme based on current microgrid active and reactive power requirements. In order to investigate the potentials for fuel expenditure reduction, 30 days-worth of microgrid power flow data has been collected on an isolated land-based oil drilling rig powered by a diesel generator power-plant, characterized by highly-variable active and reactive load profiles due to intermittent engagements and disengagements of high-power electric machinery such as top-drive, draw-works and mud-pump motors. The analysis has indicated that by avoiding the low-power operation of individual generators and by providing the peak power requirements (peak shaving) from a dedicated energy storage system, the power-plant fuel efficiency may be notably improved. An averaged power flow simulation model has been built, comprising the proposed rule-based power flow control strategy and the averaged model of a suitably sized battery energy storage system equipped with grid-tied power converter and state-of-charge control system. The effectiveness of the proposed rule-based strategy has been evaluated by means of computer simulation analysis based on drilling rig microgrid active and reactive power data recorded during the 30 day period. The analysis has indicated that fuel consumption of

  16. Rule-based decision making model

    International Nuclear Information System (INIS)

    Sirola, Miki

    1998-01-01

    A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

  17. Design Rules for Life Support Systems

    Science.gov (United States)

    Jones, Harry

    2002-01-01

    This paper considers some of the common assumptions and engineering rules of thumb used in life support system design. One general design rule is that the longer the mission, the more the life support system should use recycling and regenerable technologies. A more specific rule is that, if the system grows more than half the food, the food plants will supply all the oxygen needed for the crew life support. There are many such design rules that help in planning the analysis of life support systems and in checking results. These rules are typically if-then statements describing the results of steady-state, "back of the envelope," mass flow calculations. They are useful in identifying plausible candidate life support system designs and in rough allocations between resupply and resource recovery. Life support system designers should always review the design rules and make quick steady state calculations before doing detailed design and dynamic simulation. This paper develops the basis for the different assumptions and design rules and discusses how they should be used. We start top-down, with the highest level requirement to sustain human beings in a closed environment off Earth. We consider the crew needs for air, water, and food. We then discuss atmosphere leakage and recycling losses. The needs to support the crew and to make up losses define the fundamental life support system requirements. We consider the trade-offs between resupplying and recycling oxygen, water, and food. The specific choices between resupply and recycling are determined by mission duration, presence of in-situ resources, etc., and are defining parameters of life support system design.

  18. Optical Generation of Fuzzy-Based Rules

    Science.gov (United States)

    Gur, Eran; Mendlovic, David; Zalevsky, Zeev

    2002-08-01

    In the last third of the 20th century, fuzzy logic has risen from a mathematical concept to an applicable approach in soft computing. Today, fuzzy logic is used in control systems for various applications, such as washing machines, train-brake systems, automobile automatic gear, and so forth. The approach of optical implementation of fuzzy inferencing was given by the authors in previous papers, giving an extra emphasis to applications with two dominant inputs. In this paper the authors introduce a real-time optical rule generator for the dual-input fuzzy-inference engine. The paper briefly goes over the dual-input optical implementation of fuzzy-logic inferencing. Then, the concept of constructing a set of rules from given data is discussed. Next, the authors show ways to implement this procedure optically. The discussion is accompanied by an example that illustrates the transformation from raw data into fuzzy set rules.

  19. Utilización de Sistemas Basados en Reglas y en Casos para diseñar transmisiones por tornillo sinfín // Use of rules based systems and cases based systems for worm gear design

    Directory of Open Access Journals (Sweden)

    Jorge Laureano Moya‐Rodríguez

    2012-01-01

    Full Text Available Las técnicas de Inteligencia Artificial se aplican hoy en día a diferentes problemas de Ingeniería,especialmente los Sistemas Basados en el Conocimiento. Entre estos últimos los más comunes son losSistemas Basados en Patrones, los Sistemas Basados en Reglas, los Sistemas Basados en Casos y losSistemas Híbridos. Los Sistemas Basados en Casos parten de problemas resueltos en un dominio deaplicación y mediante un proceso de adaptación, encuentran la solución a un nuevo problema. Estossistemas pueden ser usados con éxito para el diseño de engranajes, particularmente para el diseño detransmisiones por tornillo sin fin, sin embargo ello constituye un campo de las aplicaciones de laInteligencia Artificial aún inexplorada. En el presente trabajo se hace una comparación del uso de losSistemas Basados en Regla y los Sistemas Basados en Casos para el diseño de transmisiones portornillo sin fin y se muestran los resultados de la aplicación de los sistemas basados en regla al diseñoparticular de una transmisión por tornillo sin fin.Palabras claves: tornillo sin fin, engranajes, sistemas basados en casos, sistemas basados en reglas,inteligencia artificial.____________________________________________________________________________AbstractNowadays Artificial Intelligence techniques are applied successfully to different engineering problems,especially the “Knowledge Based Systems”. Among them the most common are the “Frame basedSystems”, “Rules Based Systems”, “Case Based Systems” and "Hybrid Systems". The “Case BasedSystems” (CBS analyze solved problems in an application domain and by means of a process ofadaptation; they find the solution to a new problem. These systems can be used successfully for thedesign of gears, particularly for designing worm gears; nevertheless it constitutes a field of the applicationsof artificial intelligence even unexplored. A comparison of the use of “Rules Based System” and “CasesBased

  20. Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

    Science.gov (United States)

    Tan, W Katherine; Hassanpour, Saeed; Heagerty, Patrick J; Rundell, Sean D; Suri, Pradeep; Huhdanpaa, Hannu T; James, Kathryn; Carrell, David S; Langlotz, Curtis P; Organ, Nancy L; Meier, Eric N; Sherman, Karen J; Kallmes, David F; Luetmer, Patrick H; Griffith, Brent; Nerenz, David R; Jarvik, Jeffrey G

    2018-03-28

    To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four health systems. We used a limited data set (de-identified except for dates) sampled from lumbar spine imaging reports of a prospectively assembled cohort of adults. From N = 178,333 reports, we randomly selected N = 871 to form a reference-standard dataset, consisting of N = 413 x-ray reports and N = 458 MR reports. Using standardized criteria, four spine experts annotated the presence of 26 findings, where 71 reports were annotated by all four experts and 800 were each annotated by two experts. We calculated inter-rater agreement and finding prevalence from annotated data. We randomly split the annotated data into development (80%) and testing (20%) sets. We developed an NLP system from both rule-based and machine-learned models. We validated the system using accuracy metrics such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The multirater annotated dataset achieved inter-rater agreement of Cohen's kappa > 0.60 (substantial agreement) for 25 of 26 findings, with finding prevalence ranging from 3% to 89%. In the testing sample, rule-based and machine-learned predictions both had comparable average specificity (0.97 and 0.95, respectively). The machine-learned approach had a higher average sensitivity (0.94, compared to 0.83 for rules-based), and a higher overall AUC (0.98, compared to 0.90 for rules-based). Our NLP system performed well in identifying the 26 lumbar spine findings, as benchmarked by reference-standard annotation by medical experts. Machine-learned models provided substantial gains in model sensitivity with slight loss of specificity, and overall higher AUC. Copyright © 2018 The Association of University Radiologists. All rights reserved.

  1. The CARPEDIEM Algorithm: A Rule-Based System for Identifying Heart Failure Phenotype with a Precision Public Health Approach

    Directory of Open Access Journals (Sweden)

    Michela Franchini

    2018-01-01

    Full Text Available Modern medicine remains dependent on the accurate evaluation of a patient’s health state, recognizing that disease is a process that evolves over time and interacts with many factors unique to that patient. The CARPEDIEM project represents a concrete attempt to address these issues by developing reproducible algorithms to support the accuracy in detection of complex diseases. This study aims to establish and validate the CARPEDIEM approach and algorithm for identifying those patients presenting with or at risk of heart failure (HF by studying 153,393 subjects in Italy, based on patient information flow databases and is not reliant on the electronic health record to accomplish its goals. The resulting algorithm has been validated in a two-stage process, comparing predicted results with (1 HF diagnosis as identified by general practitioners (GPs among the reference cohort and (2 HF diagnosis as identified by cardiologists within a randomly sampled subpopulation of 389 patients. The sources of data used to detect HF cases are numerous and were standardized for this study. The accuracy and the predictive values of the algorithm with respect to the GPs and the clinical standards are highly consistent with those from previous studies. In particular, the algorithm is more efficient in detecting the more severe cases of HF according to the GPs’ validation (specificity increases according to the number of comorbidities and external validation (NYHA: II–IV; HF severity index: 2, 3. Positive and negative predictive values reveal that the CARPEDIEM algorithm is most consistent with clinical evaluation performed in the specialist setting, while it presents a greater ability to rule out false-negative HF cases within the GP practice, probably as a consequence of the different HF prevalence in the two different care settings. Further development includes analyzing the clinical features of false-positive and -negative predictions, to explore the natural

  2. Identifying influenza-like illness presentation from unstructured general practice clinical narrative using a text classifier rule-based expert system versus a clinical expert.

    Science.gov (United States)

    MacRae, Jayden; Love, Tom; Baker, Michael G; Dowell, Anthony; Carnachan, Matthew; Stubbe, Maria; McBain, Lynn

    2015-10-06

    We designed and validated a rule-based expert system to identify influenza like illness (ILI) from routinely recorded general practice clinical narrative to aid a larger retrospective research study into the impact of the 2009 influenza pandemic in New Zealand. Rules were assessed using pattern matching heuristics on routine clinical narrative. The system was trained using data from 623 clinical encounters and validated using a clinical expert as a gold standard against a mutually exclusive set of 901 records. We calculated a 98.2 % specificity and 90.2 % sensitivity across an ILI incidence of 12.4 % measured against clinical expert classification. Peak problem list identification of ILI by clinical coding in any month was 9.2 % of all detected ILI presentations. Our system addressed an unusual problem domain for clinical narrative classification; using notational, unstructured, clinician entered information in a community care setting. It performed well compared with other approaches and domains. It has potential applications in real-time surveillance of disease, and in assisted problem list coding for clinicians. Our system identified ILI presentation with sufficient accuracy for use at a population level in the wider research study. The peak coding of 9.2 % illustrated the need for automated coding of unstructured narrative in our study.

  3. Natural representation of the deduction; applying to the temporal reasoning for expert systems based on production rules

    International Nuclear Information System (INIS)

    Baudin, Patrick

    1990-01-01

    The expert systems development within a real time context, requires both to master the necessary reasoning about the time as well as to master the necessary response time for reasoning. Although rigorous temporal logic formalisms exist, strategies for temporal reasoning are either incomplete or else imply unacceptable response times. The first part presents the logic formalism upon which is based the production system. This formalism contains a three-valued logic system with truth-valued matrix, and a deductive system with a formal system. It does a rigorous work for this no standard logic, where the notions of consistency and completeness can be studied. Its development supports itself on the will to formalise the reasoning used at the elaboration time of the strategies to make them more explicit as the natural deduction method. The second part proposes an extension for the source logic formalism to take explicitly the time into account. The approach proposed through 'TANIS', the prototype of such an expert system shell, using a natural reasoning application is proposed. It allows, at the generation time, the implementation within the expert system, of an adapted deduction strategy to the symbolic temporal reasoning which is complete and ease the determination of the response time. (author) [fr

  4. Business Rules Definition for Decision Support System Using Matrix Grammar

    Directory of Open Access Journals (Sweden)

    Eva Zámečníková

    2016-06-01

    Full Text Available This paper deals with formalization of business rules by formal grammars. In our work we focus on methods for high frequency data processing. We process data by using complex event platforms (CEP which allow to process high volume of data in nearly real time. Decision making process is contained by one level of processing of CEP. Business rules are used for decision making process description. For the business rules formalization we chose matrix grammar. The use of formal grammars is quite natural as the structure of rules and its rewriting is very similar both for the business rules and for formal grammar. In addition the matrix grammar allows to simulate dependencies and correlations between the rules. The result of this work is a model for data processing of knowledge-based decision support system described by the rules of formal grammar. This system will support the decision making in CEP. This solution may contribute to the speedup of decision making process in complex event processing and also to the formal verification of these systems.

  5. Sum rules for the quarkonium systems

    International Nuclear Information System (INIS)

    Burnel, A.; Caprasse, H.

    1980-01-01

    In the framework of the radial Schroedinger equation we derive in a very simple way sum rules relating the potential to physical quantities such as the energy eigenvalues and the square of the lth derivative of the eigenfunctions at the origin. These sum rules contain as particular cases well-known results such as the quantum version of the Clausius theorem in classical mechanics as well as Kramers's relations for the Coulomb potential. Several illustrations are given and the possibilities of applying them to the quarkonium systems are considered

  6. Rule Systems for Runtime Verification: A Short Tutorial

    Science.gov (United States)

    Barringer, Howard; Havelund, Klaus; Rydeheard, David; Groce, Alex

    In this tutorial, we introduce two rule-based systems for on and off-line trace analysis, RuleR and LogScope. RuleR is a conditional rule-based system, which has a simple and easily implemented algorithm for effective runtime verification, and into which one can compile a wide range of temporal logics and other specification formalisms used for runtime verification. Specifications can be parameterized with data, or even with specifications, allowing for temporal logic combinators to be defined. We outline a number of simple syntactic extensions of core RuleR that can lead to further conciseness of specification but still enabling easy and efficient implementation. RuleR is implemented in Java and we will demonstrate its ease of use in monitoring Java programs. LogScope is a derivation of RuleR adding a simple very user-friendly temporal logic. It was developed in Python, specifically for supporting testing of spacecraft flight software for NASA’s next 2011 Mars mission MSL (Mars Science Laboratory). The system has been applied by test engineers to analysis of log files generated by running the flight software. Detailed logging is already part of the system design approach, and hence there is no added instrumentation overhead caused by this approach. While post-mortem log analysis prevents the autonomous reaction to problems possible with traditional runtime verification, it provides a powerful tool for test automation. A new system is being developed that integrates features from both RuleR and LogScope.

  7. 基于混合DSm模型的组合规则评价体系%Combination rule evaluation system based on hybrid DSm model

    Institute of Scientific and Technical Information of China (English)

    李鸿飞; 金宏斌; 田康生

    2013-01-01

    Dezert-Smarandache (DSm)理论是一种处理不确定性数据的有效方法,如何对组合规则进行评价,从而在实际应用中选择合适的规则是一个重要的问题.结合DSm理论的特点,在考虑混合DSm模型的基础上,从合成性质、时序性质和工程可用性质3方面建立评价体系.通过算例对评价体系进行验证,得出的结论与定性分析一致,说明了评价体系的有效性,为分析、评价和应用DSm理论组合规则提供理论依据.%Dezert-Smarandache (DSm) theory is an effective method for uncertain data. It is an important issue to value different kinds of combination rules for choice. The evaluation system based on hybrid DSm model is presented. The system includes combination feature, time series feature and engineering feature. The simulation results show the availability of the evaluation system. A theoretic foundation for analysis, evaluation and application of DSm combination rules is offered.

  8. Fostering cooperation in power asymmetrical water systems by the use of direct release rules and index-based insurance schemes

    Science.gov (United States)

    Denaro, Simona; Castelletti, Andrea; Giuliani, Matteo; Characklis, Gregory W.

    2018-05-01

    In river basin systems, power asymmetry is often responsible of inefficient and unbalanced water allocations. Climate change and anthropogenic pressure will possibly exacerbate such disparities as the dominant party controls an increasingly limited shared resource. In this context, the deployment of cooperation mechanisms giving greater consideration to a balanced distribution of the benefits, while improving system-wide efficiency, may be desirable. This often implies the intervention of a third party (e.g., the river basin water authority) imposing normative constraints (e.g., a minimum release) on the party in the dominant position. However, this imposition will be more acceptable to the dominant party if coupled with some form of compensation. For a public agency, compensation may be burdensome, especially when the allowance is triggered by natural events whose timing and magnitude are highly uncertain. In this context, index-based insurance contracts may represent a viable alternative and reduce the cost of achieving socially desirable outcomes. In this paper, we develop a hybrid cooperation mechanism composed of i) a direct normative constraint imposed by a regulator, and ii) an indirect financial tool, an index-based insurance contract, to be used as a compensation measure. The approach is developed for the Lake Como multi-purpose water system, Italy: a complex Alpine river basin, supporting several hydropower reservoirs and finally flowing into a regulated lake which supplies water to several downstream uses, mostly irrigated agriculture. The system is characterized by a manifest geographic power asymmetry: the upstream hydropower companies are free to release their stored water in time irrespective of the timing of the downstream demands. This situation can lead to financial losses by the downstream users and undesirable social outcomes. Results suggest that financial instruments may offer a reliable and relatively inexpensive alternative to other forms of

  9. PRACTICAL ASPECTS OF QUALITY DATA PROCESSING AND A RULEBASED EXPERT SYSTEM FOR QUALITY OF LIFE EVALUATION

    Directory of Open Access Journals (Sweden)

    Irena L. ATANASOVA

    2014-12-01

    Full Text Available One of the most important challenges the European Union was facing at the beginning of the 21st century was to balance economic development with the improvement of quality of its citizens life. A new approach for assessing the quality of life using the ten-degree global scale is revealed in this article. The aptness of this approach to exploring the social area and determining the quality of life of people in different countries and regions are also discussed. There are being examined some practical aspects of setting up an expert system for social area.The article describes the implementation of such a system for evaluating the quality of life – QLIFEX. The expert system is an innovative research project based entirely on qualitative methods, which aims at helping in understanding of how in an era of great changes residents from different countries live and work in diverse economic organizations, and how they would rate their work and life.

  10. GRAMMAR RULE BASED INFORMATION RETRIEVAL MODEL FOR BIG DATA

    Directory of Open Access Journals (Sweden)

    T. Nadana Ravishankar

    2015-07-01

    Full Text Available Though Information Retrieval (IR in big data has been an active field of research for past few years; the popularity of the native languages presents a unique challenge in big data information retrieval systems. There is a need to retrieve information which is present in English and display it in the native language for users. This aim of cross language information retrieval is complicated by unique features of the native languages such as: morphology, compound word formations, word spelling variations, ambiguity, word synonym, other language influence and etc. To overcome some of these issues, the native language is modeled using a grammar rule based approach in this work. The advantage of this approach is that the native language is modeled and its unique features are encoded using a set of inference rules. This rule base coupled with the customized ontological system shows considerable potential and is found to show better precision and recall.

  11. Rule-based emergency action level monitor prototype

    International Nuclear Information System (INIS)

    Touchton, R.A.; Gunter, A.D.; Cain, D.

    1985-01-01

    In late 1983, the Electric Power Research Institute (EPRI) began a program to encourage and stimulate the development of artificial intelligence (AI) applications for the nuclear industry. Development of a rule-based emergency action level classification system prototype is discussed. The paper describes both the full prototype currently under development and the completed, simplified prototype

  12. Fuzzy Sets-based Control Rules for Terminating Algorithms

    Directory of Open Access Journals (Sweden)

    Jose L. VERDEGAY

    2002-01-01

    Full Text Available In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the questions on the management of the fuzziness in some optimisation models, and then of using fuzzy rules for terminating conventional algorithms are presented, discussed and analyzed. Finally, for the concrete case of the Travelling Salesman Problem, and as an illustration of determination, management and using the fuzzy rules, a new algorithm easy to implement in the Model-Base Management System of any oriented Decision Support System is shown.

  13. Medicare and Medicaid Programs; CY 2017 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements. Final rule.

    Science.gov (United States)

    2016-11-03

    This final rule updates the Home Health Prospective Payment System (HH PPS) payment rates, including the national, standardized 60-day episode payment rates, the national per-visit rates, and the non-routine medical supply (NRS) conversion factor; effective for home health episodes of care ending on or after January 1, 2017. This rule also: Implements the last year of the 4-year phase-in of the rebasing adjustments to the HH PPS payment rates; updates the HH PPS case-mix weights using the most current, complete data available at the time of rulemaking; implements the 2nd-year of a 3-year phase-in of a reduction to the national, standardized 60-day episode payment to account for estimated case-mix growth unrelated to increases in patient acuity (that is, nominal case-mix growth) between CY 2012 and CY 2014; finalizes changes to the methodology used to calculate payments made under the HH PPS for high-cost "outlier" episodes of care; implements changes in payment for furnishing Negative Pressure Wound Therapy (NPWT) using a disposable device for patients under a home health plan of care; discusses our efforts to monitor the potential impacts of the rebasing adjustments; includes an update on subsequent research and analysis as a result of the findings from the home health study; and finalizes changes to the Home Health Value-Based Purchasing (HHVBP) Model, which was implemented on January 1, 2016; and updates to the Home Health Quality Reporting Program (HH QRP).

  14. Using Rule-Based Computer Programming to Unify Communication Rules Research.

    Science.gov (United States)

    Sanford, David L.; Roach, J. W.

    This paper proposes the use of a rule-based computer programming language as a standard for the expression of rules, arguing that the adoption of a standard would enable researchers to communicate about rules in a consistent and significant way. Focusing on the formal equivalence of artificial intelligence (AI) programming to different types of…

  15. Moral empiricism and the bias for act-based rules.

    Science.gov (United States)

    Ayars, Alisabeth; Nichols, Shaun

    2017-10-01

    Previous studies on rule learning show a bias in favor of act-based rules, which prohibit intentionally producing an outcome but not merely allowing the outcome. Nichols, Kumar, Lopez, Ayars, and Chan (2016) found that exposure to a single sample violation in which an agent intentionally causes the outcome was sufficient for participants to infer that the rule was act-based. One explanation is that people have an innate bias to think rules are act-based. We suggest an alternative empiricist account: since most rules that people learn are act-based, people form an overhypothesis (Goodman, 1955) that rules are typically act-based. We report three studies that indicate that people can use information about violations to form overhypotheses about rules. In study 1, participants learned either three "consequence-based" rules that prohibited allowing an outcome or three "act-based" rules that prohibiting producing the outcome; in a subsequent learning task, we found that participants who had learned three consequence-based rules were more likely to think that the new rule prohibited allowing an outcome. In study 2, we presented participants with either 1 consequence-based rule or 3 consequence-based rules, and we found that those exposed to 3 such rules were more likely to think that a new rule was also consequence based. Thus, in both studies, it seems that learning 3 consequence-based rules generates an overhypothesis to expect new rules to be consequence-based. In a final study, we used a more subtle manipulation. We exposed participants to examples act-based or accident-based (strict liability) laws and then had them learn a novel rule. We found that participants who were exposed to the accident-based laws were more likely to think a new rule was accident-based. The fact that participants' bias for act-based rules can be shaped by evidence from other rules supports the idea that the bias for act-based rules might be acquired as an overhypothesis from the

  16. Evidence Based Cataloguing: Moving Beyond the Rules

    Directory of Open Access Journals (Sweden)

    Kathy Carter

    2010-12-01

    Full Text Available Cataloguing is sometimes regarded as a rule-bound, production-based activity that offers little scope for professional judgement and decision-making. In reality, cataloguing involves challenging decisions that can have significant service and financial impacts. The current environment for cataloguing is a maelstrom of changing demands and competing visions for the future. With information-seekers turning en masse to Google and their behaviour receiving greater attention, library vendors are offering “discovery layer” products to replace traditional OPACs, and cataloguers are examining and debating a transformed version of their descriptive cataloguing rules (Resource Description and Access or RDA. In his “Perceptions of the future of cataloging: Is the sky really falling?” (2009, Ivey provides a good summary of this environment. At the same time, myriad new metadata formats and schema are being developed and applied for digital collections in libraries and other institutions. In today’s libraries, cataloguing is no longer limited to management of traditional AACR and MARC-based metadata for traditional library collections. And like their parent institutions, libraries cannot ignore growing pressures to demonstrate accountability and tangible value provided by their services. More than ever, research and an evidence based approach can help guide cataloguing decision-making.

  17. Performance based regulation - The maintenance rule

    Energy Technology Data Exchange (ETDEWEB)

    Correia, Richard P. [NRR/DOTS/TQMP, U.S. Nuclear Regulatory Commission, Office of Nuclear Reactor Regulation, M/S OWFN 10A19, Washington, D.C. 20555 (United States)

    1997-07-01

    The U.S. Nuclear Regulatory Commission has begun a transition from 'process-oriented' to 'results-oriented' regulations. The maintenance rule is a results-oriented rule that mandates consideration of risk and plant performance. The Maintenance Rule allows licensees to devise the most effective and efficient means of achieving the results described in the rule including the use of Probabilistic Risk (or Safety) Assessments. The NRC staff conducted a series of site visits to evaluate implementation of the Rule. Conclusions from the site visits indicated that the results-oriented Maintenance Rule can be successfully implemented and enforced. (author)

  18. Performance based regulation - The maintenance rule

    International Nuclear Information System (INIS)

    Correia, Richard P.

    1997-01-01

    The U.S. Nuclear Regulatory Commission has begun a transition from 'process-oriented' to 'results-oriented' regulations. The maintenance rule is a results-oriented rule that mandates consideration of risk and plant performance. The Maintenance Rule allows licensees to devise the most effective and efficient means of achieving the results described in the rule including the use of Probabilistic Risk (or Safety) Assessments. The NRC staff conducted a series of site visits to evaluate implementation of the Rule. Conclusions from the site visits indicated that the results-oriented Maintenance Rule can be successfully implemented and enforced. (author)

  19. Efficient Encoding of Inflection Rules in NLP Systems

    Directory of Open Access Journals (Sweden)

    Péter BARABÁSS

    2012-12-01

    Full Text Available The grammatical parsing unit is a core module in natural language processing engines. This unit determines the grammatical roles of the incoming words and it converts the sentences into semantic models. A special grammar rule in agglutinative languages is the inflection rule. The traditional, automata-based parsers are usually not very effective in the parsing of inflection transformations. The paper presents implementation alternatives and compares them from the viewpoint of time efficiency and accuracy. The prototype system was tested with examples from Hungarian.

  20. A rule-based automatic sleep staging method.

    Science.gov (United States)

    Liang, Sheng-Fu; Kuo, Chin-En; Hu, Yu-Han; Cheng, Yu-Shian

    2012-03-30

    In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. On minimal inhibitory rules for almost all k-valued information systems

    KAUST Repository

    Moshkov, Mikhail

    2009-07-30

    The minimal inhibitory rules for information systems can be used for construction of classifiers. We show that almost all information systems from a certain large class of information systems have relatively short minimal inhibitory rules. However, the number of such rules is not polynomial in the number of attributes and the number of objects. This class consists of all k-valued information systems, k ≥ 2, with the number of objects polynomial in the number of attributes. Hence, for efficient construction of classifiers some filtration techniques in rule generation are necessary. Another way is to work with lazy classification algorithms based on inhibitory rules.

  2. Rule base system for identification of patients with specific critical care syndromes: The "sniffer" for acute lung injury.

    Science.gov (United States)

    Herasevich, V; Yilmaz, M; Khan, H; Chute, C G; Gajic, O

    2007-10-11

    Early detection of specific critical care syndromes, such as sepsis or acute lung injury (ALI)is essential for timely implementation of evidence based therapies. Using a near-real time copy of the electronic medical records ("ICU data mart") we developed and validated custom electronic alert (ALI"sniffer") in a cohort of 485 critically ill medical patients. Compared with the gold standard of prospective screening, ALI "sniffer" demonstrated good sensitivity, 93% (95% CI 90 to 95) and specificity, 90% (95% CI 87 to 92). It is not known if the bedside implementation of ALI "sniffer" will improve the adherence to evidence-based therapies and outcome of patients with ALI.

  3. Oxytocin modulates trait-based rule following

    NARCIS (Netherlands)

    Gross, J.; de Dreu, C.K.W.

    Rules, whether in the form of norms, taboos or laws, regulate and coordinate human life. Some rules, however, are arbitrary and adhering to them can be personally costly. Rigidly sticking to such rules can be considered maladaptive. Here, we test whether, at the neurobiological level, (mal)adaptive

  4. Derivation and Validation of a Biomarker-Based Clinical Algorithm to Rule Out Sepsis From Noninfectious Systemic Inflammatory Response Syndrome at Emergency Department Admission: A Multicenter Prospective Study.

    Science.gov (United States)

    Mearelli, Filippo; Fiotti, Nicola; Giansante, Carlo; Casarsa, Chiara; Orso, Daniele; De Helmersen, Marco; Altamura, Nicola; Ruscio, Maurizio; Castello, Luigi Mario; Colonetti, Efrem; Marino, Rossella; Barbati, Giulia; Bregnocchi, Andrea; Ronco, Claudio; Lupia, Enrico; Montrucchio, Giuseppe; Muiesan, Maria Lorenza; Di Somma, Salvatore; Avanzi, Gian Carlo; Biolo, Gianni

    2018-05-07

    To derive and validate a predictive algorithm integrating a nomogram-based prediction of the pretest probability of infection with a panel of serum biomarkers, which could robustly differentiate sepsis/septic shock from noninfectious systemic inflammatory response syndrome. Multicenter prospective study. At emergency department admission in five University hospitals. Nine-hundred forty-seven adults in inception cohort and 185 adults in validation cohort. None. A nomogram, including age, Sequential Organ Failure Assessment score, recent antimicrobial therapy, hyperthermia, leukocytosis, and high C-reactive protein values, was built in order to take data from 716 infected patients and 120 patients with noninfectious systemic inflammatory response syndrome to predict pretest probability of infection. Then, the best combination of procalcitonin, soluble phospholypase A2 group IIA, presepsin, soluble interleukin-2 receptor α, and soluble triggering receptor expressed on myeloid cell-1 was applied in order to categorize patients as "likely" or "unlikely" to be infected. The predictive algorithm required only procalcitonin backed up with soluble phospholypase A2 group IIA determined in 29% of the patients to rule out sepsis/septic shock with a negative predictive value of 93%. In a validation cohort of 158 patients, predictive algorithm reached 100% of negative predictive value requiring biomarker measurements in 18% of the population. We have developed and validated a high-performing, reproducible, and parsimonious algorithm to assist emergency department physicians in distinguishing sepsis/septic shock from noninfectious systemic inflammatory response syndrome.

  5. The driver, the road, the rules … and the rest? A systems-based approach to young driver road safety.

    Science.gov (United States)

    Scott-Parker, B; Goode, N; Salmon, P

    2015-01-01

    The persistent overrepresentation of young drivers in road crashes is universally recognised. A multitude of factors influencing their behaviour and safety have been identified through methods including crash analyses, simulated and naturalistic driving studies, and self-report measures. Across the globe numerous, diverse, countermeasures have been implemented; the design of the vast majority of these has been informed by a driver-centric approach. An alternative approach gaining popularity in transport safety is the systems approach which considers not only the characteristics of the individual, but also the decisions and actions of other actors within the road transport system, along with the interactions amongst them. This paper argues that for substantial improvements to be made in young driver road safety, what has been learnt from driver-centric research needs to be integrated into a systems approach, thus providing a holistic appraisal of the young driver road safety problem. Only then will more effective opportunities and avenues for intervention be realised. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Management and monitoring of public buildings through ICT based systems: Control rules for energy saving with lighting and HVAC services

    OpenAIRE

    Aghemo, C.; Virgone, J.; Fracastoro, G.V.; Pellegrino, A.; Blaso, L.; Savoyat, J.; Johannes, Kevyn

    2013-01-01

    The presented work addresses the topic of energy savings in existing public buildings, when no significant retrofits on building envelope or plants can be done and savings can be achieved by designing intelligent ICT-based service to monitor and control environmental conditions, energy loads and plants operation. At the end of 2010 the European Commission, within the Seventh Framework Program, has founded a project entitled “Smart Energy Efficient Middleware for Public Spaces” (SEEMPubS). To ...

  7. Rule-based expert system to establish the linkage between yarn twist factor and end-use.

    CSIR Research Space (South Africa)

    Dlodlo, N

    2009-09-01

    Full Text Available of the fibre alignment to axis. The tex twist factor αtex is defined as: where: αtex is the tex twist factor, t = twist expressed in turns/metre (or turns/centimetre), Ti = the effective linear density (count) of the composite yarn expressed in tex... of staple fibre yarns. They can be classed by fibre length (e.g. short and long staple), by spinning system (e.g. ring and rotor), or by yarn construction (e.g. single, plied, cabled, multiple and fancy). Ring-spun yarns are produced on 1000/itex Tt=α m...

  8. Guidelines for visualizing and annotating rule-based models†

    Science.gov (United States)

    Chylek, Lily A.; Hu, Bin; Blinov, Michael L.; Emonet, Thierry; Faeder, James R.; Goldstein, Byron; Gutenkunst, Ryan N.; Haugh, Jason M.; Lipniacki, Tomasz; Posner, Richard G.; Yang, Jin; Hlavacek, William S.

    2011-01-01

    Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models. PMID:21647530

  9. Guidelines for visualizing and annotating rule-based models.

    Science.gov (United States)

    Chylek, Lily A; Hu, Bin; Blinov, Michael L; Emonet, Thierry; Faeder, James R; Goldstein, Byron; Gutenkunst, Ryan N; Haugh, Jason M; Lipniacki, Tomasz; Posner, Richard G; Yang, Jin; Hlavacek, William S

    2011-10-01

    Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.

  10. Sum rules and constraints on passive systems

    International Nuclear Information System (INIS)

    Bernland, A; Gustafsson, M; Luger, A

    2011-01-01

    A passive system is one that cannot produce energy, a property that naturally poses constraints on the system. A system in convolution form is fully described by its transfer function, and the class of Herglotz functions, holomorphic functions mapping the open upper half-plane to the closed upper half-plane, is closely related to the transfer functions of passive systems. Following a well-known representation theorem, Herglotz functions can be represented by means of positive measures on the real line. This fact is exploited in this paper in order to rigorously prove a set of integral identities for Herglotz functions that relate weighted integrals of the function to its asymptotic expansions at the origin and infinity. The integral identities are the core of a general approach introduced here to derive sum rules and physical limitations on various passive physical systems. Although similar approaches have previously been applied to a wide range of specific applications, this paper is the first to deliver a general procedure together with the necessary proofs. This procedure is described thoroughly and exemplified with examples from electromagnetic theory.

  11. A forecast-based STDP rule suitable for neuromorphic implementation.

    Science.gov (United States)

    Davies, S; Galluppi, F; Rast, A D; Furber, S B

    2012-08-01

    Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network learning paradigm is Spike Timing Dependent Plasticity (STDP) which adjusts the strength of a connection in response to the time difference between the pre- and post-synaptic spikes. Approaches that relate learning features to the membrane potential of the post-synaptic neuron have emerged as possible alternatives to the more common STDP rule, with various implementations and approximations. Here we use a new type of neuromorphic hardware, SpiNNaker, which represents the flexible "neuromimetic" architecture, to demonstrate a new approach to this problem. Based on the standard STDP algorithm with modifications and approximations, a new rule, called STDP TTS (Time-To-Spike) relates the membrane potential with the Long Term Potentiation (LTP) part of the basic STDP rule. Meanwhile, we use the standard STDP rule for the Long Term Depression (LTD) part of the algorithm. We show that on the basis of the membrane potential it is possible to make a statistical prediction of the time needed by the neuron to reach the threshold, and therefore the LTP part of the STDP algorithm can be triggered when the neuron receives a spike. In our system these approximations allow efficient memory access, reducing the overall computational time and the memory bandwidth required. The improvements here presented are significant for real-time applications such as the ones for which the SpiNNaker system has been designed. We present simulation results that show the efficacy of this algorithm using one or more input patterns repeated over the whole time of the simulation. On-chip results show that

  12. A system for nonmonotonic rules on the web

    NARCIS (Netherlands)

    Antoniou, G.; Bikakis, A.; Wagner, G.R.

    2004-01-01

    Defeasible reasoning is a rule-based approach for efficient reasoning with incomplete and inconsistent information. Such reasoning is, among others, useful for ontology integration, where conflicting information arises naturally; and for the modeling of business rules and policies, where rules with

  13. A rule-based software test data generator

    Science.gov (United States)

    Deason, William H.; Brown, David B.; Chang, Kai-Hsiung; Cross, James H., II

    1991-01-01

    Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

  14. A Rules-Based Simulation of Bacterial Turbulence

    Science.gov (United States)

    Mikel-Stites, Maxwell; Staples, Anne

    2015-11-01

    In sufficiently dense bacterial populations (>40% bacteria by volume), unusual collective swimming behaviors have been consistently observed, resembling von Karman vortex streets. The source of these collective swimming behavior has yet to be fully determined, and as of yet, no research has been conducted that would define whether or not this behavior is derived predominantly from the properties of the surrounding media, or if it is an emergent behavior as a result of the ``rules'' governing the behavior of individual bacteria. The goal of this research is to ascertain whether or not it is possible to design a simulation that can replicate the qualitative behavior of the densely packed bacterial populations using only behavioral rules to govern the actions of each bacteria, with the physical properties of the media being neglected. The results of the simulation will address whether or not it is possible for the system's overall behavior to be driven exclusively by these rule-based dynamics. In order to examine this, the behavioral simulation was written in MATLAB on a fixed grid, and updated sequentially with the bacterial behavior, including randomized tumbling, gathering and perceptual sub-functions. If the simulation is successful, it will serve as confirmation that it is possible to generate these qualitatively vortex-like behaviors without specific physical media (that the phenomena arises in emergent fashion from behavioral rules), or as evidence that the observed behavior requires some specific set of physical parameters.

  15. Association-rule-based tuberculosis disease diagnosis

    Science.gov (United States)

    Asha, T.; Natarajan, S.; Murthy, K. N. B.

    2010-02-01

    Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air and attacks low immune bodies such as patients with Human Immunodeficiency Virus (HIV). This work focuses on finding close association rules, a promising technique in Data Mining, within TB data. The proposed method first normalizes of raw data from medical records which includes categorical, nominal and continuous attributes and then determines Association Rules from the normalized data with different support and confidence. Association rules are applied on a real data set containing medical records of patients with TB obtained from a state hospital. The rules determined describes close association between one symptom to another; as an example, likelihood that an occurrence of sputum is closely associated with blood cough and HIV.

  16. Rule-based energy management strategies for hybrid vehicles

    NARCIS (Netherlands)

    Hofman, T.; Druten, van R.M.; Serrarens, A.F.A.; Steinbuch, M.

    2007-01-01

    Int. J. of Electric and Hybrid Vehicles (IJEHV), The highest control layer of a (hybrid) vehicular drive train is termed the Energy Management Strategy (EMS). In this paper an overview of different control methods is given and a new rule-based EMS is introduced based on the combination of Rule-Based

  17. A high-level language for rule-based modelling.

    Science.gov (United States)

    Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D

    2015-01-01

    Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

  18. Rough set and rule-based multicriteria decision aiding

    Directory of Open Access Journals (Sweden)

    Roman Slowinski

    2012-08-01

    Full Text Available The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA. DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems.

  19. Sign rules for anisotropic quantum spin systems

    International Nuclear Information System (INIS)

    Bishop, R. F.; Farnell, D. J. J.; Parkinson, J. B.

    2000-01-01

    We present exact ''sign rules'' for various spin-s anisotropic spin-lattice models. It is shown that, after a simple transformation which utilizes these sign rules, the ground-state wave function of the transformed Hamiltonian is positive definite. Using these results exact statements for various expectation values of off-diagonal operators are presented, and transitions in the behavior of these expectation values are observed at particular values of the anisotropy. Furthermore, the importance of such sign rules in variational calculations and quantum Monte Carlo calculations is emphasized. This is illustrated by a simple variational treatment of a one-dimensional anisotropic spin model

  20. Prospective study of clinician-entered research data in the Emergency Department using an Internet-based system after the HIPAA Privacy Rule

    Directory of Open Access Journals (Sweden)

    Webb William B

    2004-10-01

    Full Text Available Abstract Background Design and test the reliability of a web-based system for multicenter, real-time collection of data in the emergency department (ED, under waiver of authorization, in compliance with HIPAA. Methods This was a phase I, two-hospital study of patients undergoing evaluation for possible pulmonary embolism. Data were collected by on-duty clinicians on an HTML data collection form (prospective e-form, populated using either a personal digital assistant (PDA or personal computer (PC. Data forms were uploaded to a central, offsite server using secure socket protocol transfer. Each form was assigned a unique identifier, and all PHI data were encrypted, but were password-accessible by authorized research personnel to complete a follow-up e-form. Results From April 15, 2003-April 15 2004, 1022 prospective e-forms and 605 follow-up e-forms were uploaded. Complexities of PDA use compelled clinicians to use PCs in the ED for data entry for most forms. No data were lost and server log query revealed no unauthorized entry. Prospectively obtained PHI data, encrypted upon server upload, were successfully decrypted using password-protected access to allow follow-up without difficulty in 605 cases. Non-PHI data from prospective and follow-up forms were available to the study investigators via standard file transfer protocol. Conclusions Data can be accurately collected from on-duty clinicians in the ED using real-time, PC-Internet data entry in compliance with the Privacy Rule. Deidentification-reidentification of PHI was successfully accomplished by a password-protected encryption-deencryption mechanism to permit follow-up by approved research personnel.

  1. Constructing rule-based models using the belief functions framework

    NARCIS (Netherlands)

    Almeida, R.J.; Denoeux, T.; Kaymak, U.; Greco, S.; Bouchon-Meunier, B.; Coletti, G.; Fedrizzi, M.; Matarazzo, B.; Yager, R.R.

    2012-01-01

    Abstract. We study a new approach to regression analysis. We propose a new rule-based regression model using the theoretical framework of belief functions. For this purpose we use the recently proposed Evidential c-means (ECM) to derive rule-based models solely from data. ECM allocates, for each

  2. A hierarchical fuzzy rule-based approach to aphasia diagnosis.

    Science.gov (United States)

    Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

    2007-10-01

    Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

  3. System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

    Science.gov (United States)

    Nieten, Joseph L.; Burke, Roger

    1993-03-01

    The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

  4. An XML-Based Manipulation and Query Language for Rule-Based Information

    Science.gov (United States)

    Mansour, Essam; Höpfner, Hagen

    Rules are utilized to assist in the monitoring process that is required in activities, such as disease management and customer relationship management. These rules are specified according to the application best practices. Most of research efforts emphasize on the specification and execution of these rules. Few research efforts focus on managing these rules as one object that has a management life-cycle. This paper presents our manipulation and query language that is developed to facilitate the maintenance of this object during its life-cycle and to query the information contained in this object. This language is based on an XML-based model. Furthermore, we evaluate the model and language using a prototype system applied to a clinical case study.

  5. Autonomous Rule Based Robot Navigation In Orchards

    DEFF Research Database (Denmark)

    Andersen, Jens Christian; Ravn, Ole; Andersen, Nils Axel

    2010-01-01

    Orchard navigation using sensor-based localization and exible mission management facilitates successful missions independent of the Global Positioning System (GPS). This is especially important while driving between tight tree rows where the GPS coverage is poor. This paper suggests localization ...

  6. Biometric image enhancement using decision rule based image fusion techniques

    Science.gov (United States)

    Sagayee, G. Mary Amirtha; Arumugam, S.

    2010-02-01

    Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.

  7. Formulation of the verbal thought process based on generative rules

    Energy Technology Data Exchange (ETDEWEB)

    Suehiro, N; Fujisaki, H

    1984-01-01

    As assumption is made on the generative nature of the verbal thought process, based on an analogy between language use and verbal thought. A procedure is then presented for acquiring the set of generative rules from a given set of concept strings, leading to an efficient representation of verbal knowledge. The non-terminal symbols derived in the acquisition process are found to correspond to concepts and superordinate concepts in the human process of verbal thought. The validity of the formulation and the efficiency of knowledge representation is demonstrated by an example in which knowledge of biological properties of animals is reorganized into a set of generative rules. The process of inductive inference is then defined as a generalization of the acquired knowledge, and the principle of maximum simplicity of rules is proposed as a possible criterion for such generalization. The proposal is also tested by an example in which only a small part of a systematic body of knowledge is utilized to make interferences on the unknown parts of the system. 6 references.

  8. Changing from a Rules-based to a Principles-based Accounting Logic: A Review

    Directory of Open Access Journals (Sweden)

    Marta Silva Guerreiro

    2014-06-01

    Full Text Available We explore influences on unlisted companies when Portugal moved from a code law, rules-based accounting system, to a principles-based accounting system of adapted International Financial Reporting Standards (IFRS. Institutionalisation of the new principles-based system was generally facilitated by a socio-economic and political context that increasingly supported IFRS logic. This helped central actors gain political opportunity, mobilise important allies, and accommodate major protagonists. The preparedness of unlisted companies to adopt the new IFRS-based accounting system voluntarily was explained by their desire to maintain social legitimacy. However, it was affected negatively by the embeddedness of rule-based practices in the ‘old’ prevailing institutional logic.

  9. Connecting clinical and actuarial prediction with rule-based methods.

    Science.gov (United States)

    Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

    2015-06-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

  10. Influence of dispatching rules on average production lead time for multi-stage production systems.

    Science.gov (United States)

    Hübl, Alexander; Jodlbauer, Herbert; Altendorfer, Klaus

    2013-08-01

    In this paper the influence of different dispatching rules on the average production lead time is investigated. Two theorems based on covariance between processing time and production lead time are formulated and proved theoretically. Theorem 1 links the average production lead time to the "processing time weighted production lead time" for the multi-stage production systems analytically. The influence of different dispatching rules on average lead time, which is well known from simulation and empirical studies, can be proved theoretically in Theorem 2 for a single stage production system. A simulation study is conducted to gain more insight into the influence of dispatching rules on average production lead time in a multi-stage production system. We find that the "processing time weighted average production lead time" for a multi-stage production system is not invariant of the applied dispatching rule and can be used as a dispatching rule independent indicator for single-stage production systems.

  11. Automatic Learning of Fine Operating Rules for Online Power System Security Control.

    Science.gov (United States)

    Sun, Hongbin; Zhao, Feng; Wang, Hao; Wang, Kang; Jiang, Weiyong; Guo, Qinglai; Zhang, Boming; Wehenkel, Louis

    2016-08-01

    Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min.

  12. Optimistic Selection Rule Better Than Majority Voting System

    Science.gov (United States)

    Sugiyama, Takuya; Obata, Takuya; Hoki, Kunihito; Ito, Takeshi

    A recently proposed ensemble approach to game-tree search has attracted a great deal of attention. The ensemble system consists of M computer players, where each player uses a different series of pseudo-random numbers. A combination of multiple players under the majority voting system would improve the performance of a Shogi-playing computer. We present a new strategy of move selection based on the search values of a number of players. The move decision is made by selecting one player from all M players. Each move is selected by referring to the evaluation value of the tree search of each player. The performance and mechanism of the strategy are examined. We show that the optimistic selection rule, which selects the player that yields the highest evaluation value, outperforms the majority voting system. By grouping 16 or more computer players straightforwardly, the winning rates of the strongest Shogi programs increase from 50 to 60% or even higher.

  13. Coordinating rule-based and system-wide model predictive control strategies to reduce storage expansion of combined urban drainage systems: The case study of Lundtofte, Denmark

    DEFF Research Database (Denmark)

    Meneses, Elbys Jose; Gaussens, Marion; Jakobsen, Carsten

    2018-01-01

    performance in terms of combined sewer overflow (CSO) volumes, environmental impacts, and utility costs, which were reduced by up to 10%. The risk-based optimization strategy provided slightly better performance in terms of reducing CSO volumes, with evident improvements in environmental impacts and utility...... a five-year period. This study illustrates that including RTC during the planning stages reduces the infrastructural costs while offering better environmental protection, and that dynamic risk-based optimisation allows prioritising environmental impact reduction for particularly sensitive locations....

  14. Medicare and Medicaid Programs; CY 2018 Home Health Prospective Payment System Rate Update and CY 2019 Case-Mix Adjustment Methodology Refinements; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements. Final rule.

    Science.gov (United States)

    2017-11-07

    This final rule updates the home health prospective payment system (HH PPS) payment rates, including the national, standardized 60-day episode payment rates, the national per-visit rates, and the non-routine medical supply (NRS) conversion factor, effective for home health episodes of care ending on or after January 1, 2018. This rule also: Updates the HH PPS case-mix weights using the most current, complete data available at the time of rulemaking; implements the third year of a 3-year phase-in of a reduction to the national, standardized 60-day episode payment to account for estimated case-mix growth unrelated to increases in patient acuity (that is, nominal case-mix growth) between calendar year (CY) 2012 and CY 2014; and discusses our efforts to monitor the potential impacts of the rebasing adjustments that were implemented in CY 2014 through CY 2017. In addition, this rule finalizes changes to the Home Health Value-Based Purchasing (HHVBP) Model and to the Home Health Quality Reporting Program (HH QRP). We are not finalizing the implementation of the Home Health Groupings Model (HHGM) in this final rule.

  15. Fuzzy rule-based model for hydropower reservoirs operation

    Energy Technology Data Exchange (ETDEWEB)

    Moeini, R.; Afshar, A.; Afshar, M.H. [School of Civil Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

    2011-02-15

    Real-time hydropower reservoir operation is a continuous decision-making process of determining the water level of a reservoir or the volume of water released from it. The hydropower operation is usually based on operating policies and rules defined and decided upon in strategic planning. This paper presents a fuzzy rule-based model for the operation of hydropower reservoirs. The proposed fuzzy rule-based model presents a set of suitable operating rules for release from the reservoir based on ideal or target storage levels. The model operates on an 'if-then' principle, in which the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. In this paper, reservoir storage, inflow, and period are used as premises and the release as the consequence. The steps involved in the development of the model include, construction of membership functions for the inflow, storage and the release, formulation of fuzzy rules, implication, aggregation and defuzzification. The required knowledge bases for the formulation of the fuzzy rules is obtained form a stochastic dynamic programming (SDP) model with a steady state policy. The proposed model is applied to the hydropower operation of ''Dez'' reservoir in Iran and the results are presented and compared with those of the SDP model. The results indicate the ability of the method to solve hydropower reservoir operation problems. (author)

  16. Decision fusion recognition based on modified evidence rule

    Institute of Scientific and Technical Information of China (English)

    黎湘; 刘永祥; 付耀文; 庄钊文

    2001-01-01

    A modified evidence combination rule with a combination parameter λ is proposed to solve some problems in D-S theory by considering the correlation and complement among the evidences as well as the size and intersection of subsets in evidence. It can get reasonable results even the evidences are conflicting. Applying this rule to the real infrared/millimetre wave fusion system, a satisfactory result has been obtained.

  17. Rule-based model of vein graft remodeling.

    Directory of Open Access Journals (Sweden)

    Minki Hwang

    Full Text Available When vein segments are implanted into the arterial system for use in arterial bypass grafting, adaptation to the higher pressure and flow of the arterial system is accomplished thorough wall thickening and expansion. These early remodeling events have been found to be closely coupled to the local hemodynamic forces, such as shear stress and wall tension, and are believed to be the foundation for later vein graft failure. To further our mechanistic understanding of the cellular and extracellular interactions that lead to global changes in tissue architecture, a rule-based modeling method is developed through the application of basic rules of behaviors for these molecular and cellular activities. In the current method, smooth muscle cell (SMC, extracellular matrix (ECM, and monocytes are selected as the three components that occupy the elements of a grid system that comprise the developing vein graft intima. The probabilities of the cellular behaviors are developed based on data extracted from in vivo experiments. At each time step, the various probabilities are computed and applied to the SMC and ECM elements to determine their next physical state and behavior. One- and two-dimensional models are developed to test and validate the computational approach. The importance of monocyte infiltration, and the associated effect in augmenting extracellular matrix deposition, was evaluated and found to be an important component in model development. Final model validation is performed using an independent set of experiments, where model predictions of intimal growth are evaluated against experimental data obtained from the complex geometry and shear stress patterns offered by a mid-graft focal stenosis, where simulation results show good agreements with the experimental data.

  18. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  19. Implementing a Rule-Based Contract Compliance Checker

    Science.gov (United States)

    Strano, Massimo; Molina-Jimenez, Carlos; Shrivastava, Santosh

    The paper describes the design and implementation of an independent, third party contract monitoring service called Contract Compliance Checker (CCC). The CCC is provided with the specification of the contract in force, and is capable of observing and logging the relevant business-to-business (B2B) interaction events, in order to determine whether the actions of the business partners are consistent with the contract. A contract specification language called EROP (for Events, Rights, Obligations and Prohibitions) for the CCC has been developed based on business rules, that provides constructs to specify what rights, obligation and prohibitions become active and inactive after the occurrence of events related to the execution of business operations. The system has been designed to work with B2B industry standards such as ebXML and RosettaNet.

  20. Impact of Operating Rules on Planning Capacity Expansion of Urban Water Supply Systems

    Science.gov (United States)

    de Neufville, R.; Galelli, S.; Tian, X.

    2017-12-01

    This study addresses the impact of operating rules on capacity planning of urban water supply systems. The continuous growth of metropolitan areas represents a major challenge for water utilities, which often rely on industrial water supply (e.g., desalination, reclaimed water) to complement natural resources (e.g., reservoirs). These additional sources increase the reliability of supply, equipping operators with additional means to hedge against droughts. How do their rules for using industrial water supply impact the performance of water supply system? How might it affect long-term plans for capacity expansion? Possibly significantly, as demonstrated by the analysis of the operations and planning of a water supply system inspired by Singapore. Our analysis explores the system dynamics under multiple inflow and management scenarios to understand the extent to which alternative operating rules for the use of industrial water supply affect system performance. Results first show that these operating rules can have significant impact on the variability in system performance (e.g., reliability, energy use) comparable to that of hydro-climatological conditions. Further analyses of several capacity expansion exercises—based on our original hydrological and management scenarios—show that operating rules significantly affect the timing and magnitude of critical decisions, such as the construction of new desalination plants. These results have two implications: Capacity expansion analysis should consider the effect of a priori uncertainty about operating rules; and operators should consider how their flexibility in operating rules can affect their perceived need for capacity.

  1. Constructing compact Takagi-Sugeno rule systems: identification of complex interactions in epidemiological data.

    Science.gov (United States)

    Zhou, Shang-Ming; Lyons, Ronan A; Brophy, Sinead; Gravenor, Mike B

    2012-01-01

    The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and ω-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data.

  2. Rule-Based Storytelling Text-to-Speech (TTS Synthesis

    Directory of Open Access Journals (Sweden)

    Ramli Izzad

    2016-01-01

    Full Text Available In recent years, various real life applications such as talking books, gadgets and humanoid robots have drawn the attention to pursue research in the area of expressive speech synthesis. Speech synthesis is widely used in various applications. However, there is a growing need for an expressive speech synthesis especially for communication and robotic. In this paper, global and local rule are developed to convert neutral to storytelling style speech for the Malay language. In order to generate rules, modification of prosodic parameters such as pitch, intensity, duration, tempo and pauses are considered. Modification of prosodic parameters is examined by performing prosodic analysis on a story collected from an experienced female and male storyteller. The global and local rule is applied in sentence level and synthesized using HNM. Subjective tests are conducted to evaluate the synthesized storytelling speech quality of both rules based on naturalness, intelligibility, and similarity to the original storytelling speech. The results showed that global rule give a better result than local rule

  3. Medicare Program; Merit-Based Incentive Payment System (MIPS) and Alternative Payment Model (APM) Incentive Under the Physician Fee Schedule, and Criteria for Physician-Focused Payment Models. Final rule with comment period.

    Science.gov (United States)

    2016-11-04

    The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) repeals the Medicare sustainable growth rate (SGR) methodology for updates to the physician fee schedule (PFS) and replaces it with a new approach to payment called the Quality Payment Program that rewards the delivery of high-quality patient care through two avenues: Advanced Alternative Payment Models (Advanced APMs) and the Merit-based Incentive Payment System (MIPS) for eligible clinicians or groups under the PFS. This final rule with comment period establishes incentives for participation in certain alternative payment models (APMs) and includes the criteria for use by the Physician-Focused Payment Model Technical Advisory Committee (PTAC) in making comments and recommendations on physician-focused payment models (PFPMs). Alternative Payment Models are payment approaches, developed in partnership with the clinician community, that provide added incentives to deliver high-quality and cost-efficient care. APMs can apply to a specific clinical condition, a care episode, or a population. This final rule with comment period also establishes the MIPS, a new program for certain Medicare-enrolled practitioners. MIPS will consolidate components of three existing programs, the Physician Quality Reporting System (PQRS), the Physician Value-based Payment Modifier (VM), and the Medicare Electronic Health Record (EHR) Incentive Program for Eligible Professionals (EPs), and will continue the focus on quality, cost, and use of certified EHR technology (CEHRT) in a cohesive program that avoids redundancies. In this final rule with comment period we have rebranded key terminology based on feedback from stakeholders, with the goal of selecting terms that will be more easily identified and understood by our stakeholders.

  4. Fuzzy Rules for Ant Based Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Amira Hamdi

    2016-01-01

    Full Text Available This paper provides a new intelligent technique for semisupervised data clustering problem that combines the Ant System (AS algorithm with the fuzzy c-means (FCM clustering algorithm. Our proposed approach, called F-ASClass algorithm, is a distributed algorithm inspired by foraging behavior observed in ant colonyT. The ability of ants to find the shortest path forms the basis of our proposed approach. In the first step, several colonies of cooperating entities, called artificial ants, are used to find shortest paths in a complete graph that we called graph-data. The number of colonies used in F-ASClass is equal to the number of clusters in dataset. Hence, the partition matrix of dataset founded by artificial ants is given in the second step, to the fuzzy c-means technique in order to assign unclassified objects generated in the first step. The proposed approach is tested on artificial and real datasets, and its performance is compared with those of K-means, K-medoid, and FCM algorithms. Experimental section shows that F-ASClass performs better according to the error rate classification, accuracy, and separation index.

  5. Automatic detection of esophageal pressure events. Is there an alternative to rule-based criteria?

    DEFF Research Database (Denmark)

    Kruse-Andersen, S; Rütz, K; Kolberg, Jens Godsk

    1995-01-01

    of relevant pressure peaks at the various recording levels. Until now, this selection has been performed entirely by rule-based systems, requiring each pressure deflection to fit within predefined rigid numerical limits in order to be detected. However, due to great variations in the shapes of the pressure...... curves generated by muscular contractions, rule-based criteria do not always select the pressure events most relevant for further analysis. We have therefore been searching for a new concept for automatic event recognition. The present study describes a new system, based on the method of neurocomputing.......79-0.99 and accuracies of 0.89-0.98, depending on the recording level within the esophageal lumen. The neural networks often recognized peaks that clearly represented true contractions but that had been rejected by a rule-based system. We conclude that neural networks have potentials for automatic detections...

  6. Combination Rules for Morse-Based van der Waals Force Fields.

    Science.gov (United States)

    Yang, Li; Sun, Lei; Deng, Wei-Qiao

    2018-02-15

    In traditional force fields (FFs), van der Waals interactions have been usually described by the Lennard-Jones potentials. Conventional combination rules for the parameters of van der Waals (VDW) cross-termed interactions were developed for the Lennard-Jones based FFs. Here, we report that the Morse potentials were a better function to describe VDW interactions calculated by highly precise quantum mechanics methods. A new set of combination rules was developed for Morse-based FFs, in which VDW interactions were described by Morse potentials. The new set of combination rules has been verified by comparing the second virial coefficients of 11 noble gas mixtures. For all of the mixed binaries considered in this work, the combination rules work very well and are superior to all three other existing sets of combination rules reported in the literature. We further used the Morse-based FF by using the combination rules to simulate the adsorption isotherms of CH 4 at 298 K in four covalent-organic frameworks (COFs). The overall agreement is great, which supports the further applications of this new set of combination rules in more realistic simulation systems.

  7. Enhancing reliable online transaction with intelligent rule-based ...

    African Journals Online (AJOL)

    Enhancing reliable online transaction with intelligent rule-based fraud detection technique. ... These are with a bid to reducing amongst other things the cost of production and also dissuade the poor handling of Nigeria currency. The CBN pronouncement has necessitated the upsurge in transactions completed with credit ...

  8. Good and Bad Objects : Cardinality-Based Rules

    NARCIS (Netherlands)

    Dimitrov, D.A.; Borm, P.E.M.; Hendrickx, R.L.P.

    2003-01-01

    We consider the problem of ranking sets of objects, the members of which are mutually compatible.Assuming that each object is either good or bad, we axiomatically characterize three cardinality-based rules which arise naturally in this dichotomous setting.They are what we call the symmetric

  9. Rule-based Test Generation with Mind Maps

    Directory of Open Access Journals (Sweden)

    Dimitry Polivaev

    2012-02-01

    Full Text Available This paper introduces basic concepts of rule based test generation with mind maps, and reports experiences learned from industrial application of this technique in the domain of smart card testing by Giesecke & Devrient GmbH over the last years. It describes the formalization of test selection criteria used by our test generator, our test generation architecture and test generation framework.

  10. Optimal Sequential Rules for Computer-Based Instruction.

    Science.gov (United States)

    Vos, Hans J.

    1998-01-01

    Formulates sequential rules for adapting the appropriate amount of instruction to learning needs in the context of computer-based instruction. Topics include Bayesian decision theory, threshold and linear-utility structure, psychometric model, optimal sequential number of test questions, and an empirical example of sequential instructional…

  11. Radiological protection national system. Basic security rules

    International Nuclear Information System (INIS)

    1981-01-01

    This work has been prepared as the first one of a set of standards and regulations that will be enforced to provide the protection of men and the environment against the undesirable effects of ionizing radiations. It establishes, in the first place, the system of dose limits for the country and the principles of its utilization. It takes into account the CIPR's recommendations in this area and the mentioned frame of reference, it establishes further the necessary restrictions for the application of the limits to the professionally exposed workers, as well as to the isolated members of the public and the population in general. In addition it establishes the general conditions to be met for the implementation of radiological protection, among them, the classification of working areas and working conditions as well as the compulsory periodical medical surveillance. (H.D.N.)

  12. Design Transformations for Rule-based Procedural Modeling

    KAUST Repository

    Lienhard, Stefan; Lau, Cheryl; Mü ller, Pascal; Wonka, Peter; Pauly, Mark

    2017-01-01

    We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

  13. Design Transformations for Rule-based Procedural Modeling

    KAUST Repository

    Lienhard, Stefan

    2017-05-24

    We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

  14. Knowledge rule base for the beam optics program TRACE 3-D

    International Nuclear Information System (INIS)

    Gillespie, G.H.; Van Staagen, P.K.; Hill, B.W.

    1993-01-01

    An expert system type of knowledge rule base has been developed for the input parameters used by the particle beam transport program TRACE 3-D. The goal has been to provide the program's user with adequate on-screen information to allow him to initially set up a problem with minimal open-quotes off-lineclose quotes calculations. The focus of this work has been in developing rules for the parameters which define the beam line transport elements. Ten global parameters, the particle mass and charge, beam energy, etc., are used to provide open-quotes expertclose quotes estimates of lower and upper limits for each of the transport element parameters. For example, the limits for the field strength of the quadrupole element are based on a water-cooled, iron-core electromagnet with dimensions derived from practical engineering constraints, and the upper limit for the effective length is scaled with the particle momenta so that initially parallel trajectories do not cross the axis inside the magnet. Limits for the quadrupole doublet and triplet parameters incorporate these rules and additional rules based on stable FODO lattices and bidirectional focusing requirements. The structure of the rule base is outlined and examples for the quadrupole singlet, doublet and triplet are described. The rule base has been implemented within the Shell for Particle Accelerator Related Codes (SPARC) graphical user interface (GUI)

  15. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic...

  16. Modeling reliability measurement of interface on information system: Towards the forensic of rules

    Science.gov (United States)

    Nasution, M. K. M.; Sitompul, Darwin; Harahap, Marwan

    2018-02-01

    Today almost all machines depend on the software. As a software and hardware system depends also on the rules that are the procedures for its use. If the procedure or program can be reliably characterized by involving the concept of graph, logic, and probability, then regulatory strength can also be measured accordingly. Therefore, this paper initiates an enumeration model to measure the reliability of interfaces based on the case of information systems supported by the rules of use by the relevant agencies. An enumeration model is obtained based on software reliability calculation.

  17. System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation. [applied to Shuttle Mission Simulator

    Science.gov (United States)

    Nieten, Joseph; Burke, Roger

    1993-01-01

    Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, and used to drive the rule generation process. These rule bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

  18. Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization

    Science.gov (United States)

    Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

    2016-01-01

    Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. Availability and implementation: The annotation ontology for rule-based models can be found at http

  19. Electromagnetic compatibility design and cabling system rules; Regles de conception et de cablage des systemes electroniques

    Energy Technology Data Exchange (ETDEWEB)

    Raimbourg, J.

    2009-07-01

    This report is devoted to establish EMC (Electromagnetic Compatibility) design and cabling system rules. It is intended for hardware designers in charge of designing electronic maps or integrating existing materials into a comprehensive system. It is a practical guide. The rules described in this document do not require enhanced knowledge of advanced mathematical or physical concepts. The key point is to understand phenomena with a pragmatic approach to highlight the design and protection rules. (author)

  20. Rule Induction-Based Knowledge Discovery for Energy Efficiency

    OpenAIRE

    Chen, Qipeng; Fan, Zhong; Kaleshi, Dritan; Armour, Simon M D

    2015-01-01

    Rule induction is a practical approach to knowledge discovery. Provided that a problem is developed, rule induction is able to return the knowledge that addresses the goal of this problem as if-then rules. The primary goals of knowledge discovery are for prediction and description. The rule format knowledge representation is easily understandable so as to enable users to make decisions. This paper presents the potential of rule induction for energy efficiency. In particular, three rule induct...

  1. Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

    KAUST Repository

    Delimata, Paweł

    2010-01-01

    We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their right hand sides). Contrary to this, any rule of the second kind, called as a bounded nondeterministic rule, can have on the right hand side only a few decisions. We show that both kinds of rules can be used for improving the quality of classification. In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules. We also present an application of bounded nondeterministic rules in construction of rule based classifiers. We include the results of experiments showing that by combining rule based classifiers based on minimal decision rules with bounded nondeterministic rules having confidence close to 1 and sufficiently large support, it is possible to improve the classification quality. © 2010 Springer-Verlag.

  2. On minimal inhibitory rules for almost all k-valued information systems

    KAUST Repository

    Moshkov, Mikhail; Skowron, Andrzej; Suraj, Zbigniew

    2009-01-01

    The minimal inhibitory rules for information systems can be used for construction of classifiers. We show that almost all information systems from a certain large class of information systems have relatively short minimal inhibitory rules. However

  3. From Mozart to MIDI : A Rule System for Expressive Articulation

    OpenAIRE

    Hähnel, Tilo

    2010-01-01

    The propriety of articulation, especially of notes that lackannotations, is influenced by the origin of the particularmusic. This paper presents a rule system for articulationderived from late Baroque and early Classic treatises on performance. Expressive articulation, in this respect, is understood as a combination of alterable tone features like duration, loudness, and timbre. The model differentiates globalcharacteristics and local particularities, provides a generalframework for human-lik...

  4. Improved Personalized Recommendation Based on Causal Association Rule and Collaborative Filtering

    Science.gov (United States)

    Lei, Wu; Qing, Fang; Zhou, Jin

    2016-01-01

    There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

  5. Attempts to Dodge Drowning in Data : Rule- and Risk-Based Anti Money Laundering Policies Compared

    NARCIS (Netherlands)

    Unger, B.; van Waarden, F.

    Both in the US and in Europe anti money laundering policy switched from a rule-to a risk-based reporting system in order to avoid over-reporting by the private sector. However, reporting increased in most countries, while the quality of information decreased. Governments drowned in data because

  6. Design rules and reality check for carbon-based ultracapacitors

    Science.gov (United States)

    Eisenmann, Erhard T.

    1995-04-01

    Design criteria for carbon-based Ultracapacitors have been determined for specified energy and power requirements, using the geometry of the components and such material properties as density, porosity and conductivity as parameters, while also considering chemical compatibility. This analysis shows that the weights of active and inactive components of the capacitor structure must be carefully balanced for maximum energy and power density. When applied to nonaqueous electrolytes, the design rules for a 5 Wh/kg device call for porous carbon with a specific capacitance of about 30 F/cu cm. This performance is not achievable with pure, electrostatic double layer capacitance. Double layer capacitance is only 5 to 30% of that observed in aqueous electrolyte. Tests also showed that nonaqueous electrolytes have a diminished capability to access micropores in activated carbon, in one case yielding a capacitance of less than 1 F/cu cm for carbon that had 100 F/cu cm in aqueous electrolyte. With negative results on nonaqueous electrolytes dominating the present study, the obvious conclusion is to concentrate on aqueous systems. Only aqueous double layer capacitors offer adequate electrostatic charging characteristics which is the basis for high power performance. There arc many opportunities for further advancing aqueous double layer capacitors, one being the use of highly activated carbon films, as opposed to powders, fibers and foams. While the manufacture of carbon films is still costly, and while the energy and power density of the resulting devices may not meet the optimistic goals that have been proposed, this technology could produce true double layer capacitors with significantly improved performance and large commercial potential.

  7. Functional networks inference from rule-based machine learning models.

    Science.gov (United States)

    Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

    2016-01-01

    Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The

  8. A rule-based stemmer for Arabic Gulf dialect

    Directory of Open Access Journals (Sweden)

    Belal Abuata

    2015-04-01

    Full Text Available Arabic dialects arewidely used from many years ago instead of Modern Standard Arabic language in many fields. The presence of dialects in any language is a big challenge. Dialects add a new set of variational dimensions in some fields like natural language processing, information retrieval and even in Arabic chatting between different Arab nationals. Spoken dialects have no standard morphological, phonological and lexical like Modern Standard Arabic. Hence, the objective of this paper is to describe a procedure or algorithm by which a stem for the Arabian Gulf dialect can be defined. The algorithm is rule based. Special rules are created to remove the suffixes and prefixes of the dialect words. Also, the algorithm applies rules related to the word size and the relation between adjacent letters. The algorithm was tested for a number of words and given a good correct stem ratio. The algorithm is also compared with two Modern Standard Arabic algorithms. The results showed that Modern Standard Arabic stemmers performed poorly with Arabic Gulf dialect and our algorithm performed poorly when applied for Modern Standard Arabic words.

  9. Methods of Information Subjects and Objects Interaction Rules Formalization in the Electronic Trading Platform System

    Directory of Open Access Journals (Sweden)

    Emma Emanuilova Yandybaeva

    2015-03-01

    Full Text Available The methods of information subjects and objects interaction rules formalization in the electronic trading platform system has been developed. They are based on mathematical model of mandatory role-based access control. As a result of the work we have defined set of user roles and constructed roles hierarchy. For the roles hierarchy restrictions have been imposed to ensure the safety of the information system.

  10. Research on Fault Diagnosis Method Based on Rule Base Neural Network

    Directory of Open Access Journals (Sweden)

    Zheng Ni

    2017-01-01

    Full Text Available The relationship between fault phenomenon and fault cause is always nonlinear, which influences the accuracy of fault location. And neural network is effective in dealing with nonlinear problem. In order to improve the efficiency of uncertain fault diagnosis based on neural network, a neural network fault diagnosis method based on rule base is put forward. At first, the structure of BP neural network is built and the learning rule is given. Then, the rule base is built by fuzzy theory. An improved fuzzy neural construction model is designed, in which the calculated methods of node function and membership function are also given. Simulation results confirm the effectiveness of this method.

  11. 77 FR 52977 - Regulatory Capital Rules: Advanced Approaches Risk-Based Capital Rule; Market Risk Capital Rule

    Science.gov (United States)

    2012-08-30

    ...-weighted assets for residential mortgages, securitization exposures, and counterparty credit risk. The.... Risk-Weighted Assets--Proposed Modifications to the Advanced Approaches Rules A. Counterparty Credit... Margin Period of Risk 3. Changes to the Internal Models Methodology (IMM) 4. Credit Valuation Adjustments...

  12. On the effects of adaptive reservoir operating rules in hydrological physically-based models

    Science.gov (United States)

    Giudici, Federico; Anghileri, Daniela; Castelletti, Andrea; Burlando, Paolo

    2017-04-01

    Recent years have seen a significant increase of the human influence on the natural systems both at the global and local scale. Accurately modeling the human component and its interaction with the natural environment is key to characterize the real system dynamics and anticipate future potential changes to the hydrological regimes. Modern distributed, physically-based hydrological models are able to describe hydrological processes with high level of detail and high spatiotemporal resolution. Yet, they lack in sophistication for the behavior component and human decisions are usually described by very simplistic rules, which might underperform in reproducing the catchment dynamics. In the case of water reservoir operators, these simplistic rules usually consist of target-level rule curves, which represent the average historical level trajectory. Whilst these rules can reasonably reproduce the average seasonal water volume shifts due to the reservoirs' operation, they cannot properly represent peculiar conditions, which influence the actual reservoirs' operation, e.g., variations in energy price or water demand, dry or wet meteorological conditions. Moreover, target-level rule curves are not suitable to explore the water system response to climate and socio economic changing contexts, because they assume a business-as-usual operation. In this work, we quantitatively assess how the inclusion of adaptive reservoirs' operating rules into physically-based hydrological models contribute to the proper representation of the hydrological regime at the catchment scale. In particular, we contrast target-level rule curves and detailed optimization-based behavioral models. We, first, perform the comparison on past observational records, showing that target-level rule curves underperform in representing the hydrological regime over multiple time scales (e.g., weekly, seasonal, inter-annual). Then, we compare how future hydrological changes are affected by the two modeling

  13. Rule-based detection of intrathoracic airway trees

    International Nuclear Information System (INIS)

    Sonka, M.; Park, W.; Hoffman, E.A.

    1996-01-01

    New sensitive and reliable methods for assessing alterations in regional lung structure and function are critically important for the investigation and treatment of pulmonary diseases. Accurate identification of the airway tree will provide an assessment of airway structure and will provide a means by which multiple volumetric images of the lung at the same lung volume over time can be used to assess regional parenchymal changes. The authors describe a novel rule-based method for the segmentation of airway trees from three-dimensional (3-D) sets of computed tomography (CT) images, and its validation. The presented method takes advantage of a priori anatomical knowledge about pulmonary airway and vascular trees and their interrelationships. The method is based on a combination of 3-D seeded region growing that is used to identify large airways, rule-based two-dimensional (2-D) segmentation of individual CT slices to identify probable locations of smaller diameter airways, and merging of airway regions across the 3-D set of slices resulting in a tree-like airway structure. The method was validated in 40 3-mm-thick CT sections from five data sets of canine lungs scanned via electron beam CT in vivo with lung volume held at a constant pressure. The method's performance was compared with that of the conventional 3-D region growing method. The method substantially outperformed an existing conventional approach to airway tree detection

  14. Decision tables and rule engines in organ allocation systems for optimal transparency and flexibility

    NARCIS (Netherlands)

    Schaafsma, M.; Deijl, W. van der; Smits, J.M.M.; Rahmel, A.O.; Vries Robbé, P.F. de; Hoitsma, A.J.

    2011-01-01

    Organ allocation systems have become complex and difficult to comprehend. We introduced decision tables to specify the rules of allocation systems for different organs. A rule engine with decision tables as input was tested for the Kidney Allocation System (ETKAS). We compared this rule engine with

  15. GraDit: graph-based data repair algorithm for multiple data edits rule violations

    Science.gov (United States)

    Ode Zuhayeni Madjida, Wa; Gusti Bagus Baskara Nugraha, I.

    2018-03-01

    Constraint-based data cleaning captures data violation to a set of rule called data quality rules. The rules consist of integrity constraint and data edits. Structurally, they are similar, where the rule contain left hand side and right hand side. Previous research proposed a data repair algorithm for integrity constraint violation. The algorithm uses undirected hypergraph as rule violation representation. Nevertheless, this algorithm can not be applied for data edits because of different rule characteristics. This study proposed GraDit, a repair algorithm for data edits rule. First, we use bipartite-directed hypergraph as model representation of overall defined rules. These representation is used for getting interaction between violation rules and clean rules. On the other hand, we proposed undirected graph as violation representation. Our experimental study showed that algorithm with undirected graph as violation representation model gave better data quality than algorithm with undirected hypergraph as representation model.

  16. Gain ratio based fuzzy weighted association rule mining classifier for ...

    Indian Academy of Sciences (India)

    association rule mining algorithm for extracting both association rules and member- .... The disadvantage of this work is in considering the generalization at each ... If the new attribute is entered, the generalization process does not consider the ...

  17. WellnessRules: A Web 3.0 Case Study in RuleML-Based Prolog-N3 Profile Interoperation

    Science.gov (United States)

    Boley, Harold; Osmun, Taylor Michael; Craig, Benjamin Larry

    An interoperation study, WellnessRules, is described, where rules about wellness opportunities are created by participants in rule languages such as Prolog and N3, and translated within a wellness community using RuleML/XML. The wellness rules are centered around participants, as profiles, encoding knowledge about their activities conditional on the season, the time-of-day, the weather, etc. This distributed knowledge base extends FOAF profiles with a vocabulary and rules about wellness group networking. The communication between participants is organized through Rule Responder, permitting wellness-profile translation and distributed querying across engines. WellnessRules interoperates between rules and queries in the relational (Datalog) paradigm of the pure-Prolog subset of POSL and in the frame (F-logic) paradigm of N3. An evaluation of Rule Responder instantiated for WellnessRules revealed acceptable Web response times.

  18. Method for automatic control rod operation using rule-based control

    International Nuclear Information System (INIS)

    Kinoshita, Mitsuo; Yamada, Naoyuki; Kiguchi, Takashi

    1988-01-01

    An automatic control rod operation method using rule-based control is proposed. Its features are as follows: (1) a production system to recognize plant events, determine control actions and realize fast inference (fast selection of a suitable production rule), (2) use of the fuzzy control technique to determine quantitative control variables. The method's performance was evaluated by simulation tests on automatic control rod operation at a BWR plant start-up. The results were as follows; (1) The performance which is related to stabilization of controlled variables and time required for reactor start-up, was superior to that of other methods such as PID control and program control methods, (2) the process time to select and interpret the suitable production rule, which was the same as required for event recognition or determination of control action, was short (below 1 s) enough for real time control. The results showed that the method is effective for automatic control rod operation. (author)

  19. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

    Directory of Open Access Journals (Sweden)

    Saurav Mallik

    2017-12-01

    Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  20. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

    Science.gov (United States)

    Mallik, Saurav; Zhao, Zhongming

    2017-12-28

    For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  1. Systematic construction of qualitative physics-based rules for process diagnostics

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.

    1995-01-01

    A novel first-principles-based expert system is proposed for on-line detection and identification of faulty component candidates during incipient off-normal process operations. The system performs function-oriented diagnostics and can be reused for diagnosing single-component failures in different processes and different plants through the provision of the appropriate process schematics information. The function-oriented and process-independent diagnostic features of the proposed expert system are achieved by constructing a knowledge base containing three distinct types of information, qualitative balance equation rules, functional classification of process components, and the process piping and instrumentation diagram. The various types of qualitative balance equation rules for processes utilizing single-phase liquids are derived and their usage is illustrated through simulation results of a realistic process in a nuclear power plant

  2. Optical Selection Rule of Excitons in Gapped Chiral Fermion Systems

    Science.gov (United States)

    Zhang, Xiaoou; Shan, Wen-Yu; Xiao, Di

    2018-02-01

    We show that the exciton optical selection rule in gapped chiral fermion systems is governed by their winding number w , a topological quantity of the Bloch bands. Specifically, in a CN-invariant chiral fermion system, the angular momentum of bright exciton states is given by w ±1 +n N with n being an integer. We demonstrate our theory by proposing two chiral fermion systems capable of hosting dark s -like excitons: gapped surface states of a topological crystalline insulator with C4 rotational symmetry and biased 3 R -stacked MoS2 bilayers. In the latter case, we show that gating can be used to tune the s -like excitons from bright to dark by changing the winding number. Our theory thus provides a pathway to electrical control of optical transitions in two-dimensional material.

  3. RULE-BASE METHOD FOR ANALYSIS OF QUALITY E-LEARNING IN HIGHER EDUCATION

    Directory of Open Access Journals (Sweden)

    darsih darsih darsih

    2016-04-01

    Full Text Available ABSTRACT Assessing the quality of e-learning courses to measure the success of e-learning systems in online learning is essential. The system can be used to improve education. The study analyzes the quality of e-learning course on the web site www.kulon.undip.ac.id used a questionnaire with questions based on the variables of ISO 9126. Penilaiann Likert scale was used with a web app. Rule-base reasoning method is used to subject the quality of e-learningyang assessed. A case study conducted in four e-learning courses with 133 sample / respondents as users of the e-learning course. From the obtained results of research conducted both for the value of e-learning from each subject tested. In addition, each e-learning courses have different advantages depending on certain variables. Keywords : E-Learning, Rule-Base, Questionnaire, Likert, Measuring.

  4. SPARQL Query Re-writing Using Partonomy Based Transformation Rules

    Science.gov (United States)

    Jain, Prateek; Yeh, Peter Z.; Verma, Kunal; Henson, Cory A.; Sheth, Amit P.

    Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology's containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query constraints and knowledge base. Our experiments were performed on completely third party datasets and queries. Evaluations were performed on Geonames dataset using questions from National Geographic Bee serialized into SPARQL and British Administrative Geography Ontology using questions from a popular trivia website. These experiments demonstrate high precision in retrieval of results and ease in writing queries.

  5. Generación automática de reglas de negocio en bases de datos para la implementación del sistema de información SIMCO (Automatic business rules generation in data bases for the implementation of the information system SIMCO

    Directory of Open Access Journals (Sweden)

    Yaisel Nuñez Arcia

    2015-12-01

    Full Text Available Spanis abstract. El diseño e implementación de sistemas informáticos para las organizaciones deben basarse en las políticas y reglas del negocio. Hoy día se considera ventajoso aplicar el enfoque de reglas de negocio en el desarrollo de sistemas de información, y de esta manera garantizar la inserción y modificación de las reglas de manera automática. Una de las formas para implementar un sistema de información usando reglas de negocio, es a través del tipo de herramienta independiente de los gestores de datos, pero que genera recursos de bases de datos. Ante la necesidad de desarrollar un sistema de información transaccional para la gestión de menús de comedores en la UCLV, se hizo necesaria una aplicación cuya interfaz de entrada realice las operaciones de inserción y actualización en una base de datos. La existencia de un conjunto de reglas de negocio que deben ser chequeadas al realizar estas operaciones, hace posible la utilización de la herramienta LPT-SQL con vistas a disminuir el esfuerzo de programación al insertar el código, que garantiza el cumplimiento de las reglas, y su posible modificación independientemente de la interfaz de usuario. English abstract The design and implementation of informatics systems for the organizations must be based in the business policies and rules. Nowadays, to apply a focus on business rules in the development of information systems is considered advantageous, hence guarantee the automatic insertion and modification of rules. One of the ways to implement an information system using business rules is through the independent tool type of the data managers, but that generates data bases resources. In view of the need to develop a transactional information system for the menus management of UCLV dining centres, an application which input interface makes the insert and update operations on a database was necessary. The existence of a set of business rules that must be checked to perform

  6. Associations between rule-based parenting practices and child screen viewing: A cross-sectional study

    Directory of Open Access Journals (Sweden)

    Joanna M. Kesten

    2015-01-01

    Conclusions: Limit setting is associated with greater SV. Collaborative rule setting may be effective for managing boys' game-console use. More research is needed to understand rule-based parenting practices.

  7. A Production-Rule Analysis System for Nuclear Plant monitoring and emergency response applications

    International Nuclear Information System (INIS)

    Ragheb, M.; Tsoukalas, L.; McDonough, T.; Parker, M.

    1987-01-01

    A Production-Rule Analysis System for Nuclear Power Plant Monitoring is presented. The signals generated by the Zion-1 Plant are considered for emergency Response applications. The integrity of the Plant Radiation, the Reactor Coolant, the Fuel Clad, and the Containment Systems, is monitored. Representation of the system is in the form of a goal-tree generating a Knowledge-Base searched by an Inference Engine functioning in the forward-chaining mode. The Gaol-tree is built from Fault-Trees based on plant operational information. The system is implemented on a VAX-8500 and is programmed in OPS-5

  8. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2013-01-01

    Full Text Available In this paper, we proposed a hybrid system to predict corporate bankruptcy. The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA, which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model. Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective. It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA, ant colony algorithm (ACA, and GACA. The average computation time of the model is 2.02 s.

  9. A partition enhanced mining algorithm for distributed association rule mining systems

    Directory of Open Access Journals (Sweden)

    A.O. Ogunde

    2015-11-01

    Full Text Available The extraction of patterns and rules from large distributed databases through existing Distributed Association Rule Mining (DARM systems is still faced with enormous challenges such as high response times, high communication costs and inability to adapt to the constantly changing databases. In this work, a Partition Enhanced Mining Algorithm (PEMA is presented to address these problems. In PEMA, the Association Rule Mining Coordinating Agent receives a request and decides the appropriate data sites, partitioning strategy and mining agents to use. The mining process is divided into two stages. In the first stage, the data agents horizontally segment the databases with small average transaction length into relatively smaller partitions based on the number of available sites and the available memory. On the other hand, databases with relatively large average transaction length were vertically partitioned. After this, Mobile Agent-Based Association Rule Mining-Agents, which are the mining agents, carry out the discovery of the local frequent itemsets. At the second stage, the local frequent itemsets were incrementally integrated by the from one data site to another to get the global frequent itemsets. This reduced the response time and communication cost in the system. Results from experiments conducted on real datasets showed that the average response time of PEMA showed an improvement over existing algorithms. Similarly, PEMA incurred lower communication costs with average size of messages exchanged lower when compared with benchmark DARM systems. This result showed that PEMA could be efficiently deployed for efficient discovery of valuable knowledge in distributed databases.

  10. Derivative-Based Trapezoid Rule for the Riemann-Stieltjes Integral

    Directory of Open Access Journals (Sweden)

    Weijing Zhao

    2014-01-01

    Full Text Available The derivative-based trapezoid rule for the Riemann-Stieltjes integral is presented which uses 2 derivative values at the endpoints. This kind of quadrature rule obtains an increase of two orders of precision over the trapezoid rule for the Riemann-Stieltjes integral and the error term is investigated. At last, the rationality of the generalization of derivative-based trapezoid rule for Riemann-Stieltjes integral is demonstrated.

  11. Depfix, a Tool for Automatic Rule-based Post-editing of SMT

    Directory of Open Access Journals (Sweden)

    Rudolf Rosa

    2014-09-01

    Full Text Available We present Depfix, an open-source system for automatic post-editing of phrase-based machine translation outputs. Depfix employs a range of natural language processing tools to obtain analyses of the input sentences, and uses a set of rules to correct common or serious errors in machine translation outputs. Depfix is currently implemented only for English-to-Czech translation direction, but extending it to other languages is planned.

  12. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

  13. Derivation of Optimal Operating Rules for Large-scale Reservoir Systems Considering Multiple Trade-off

    Science.gov (United States)

    Zhang, J.; Lei, X.; Liu, P.; Wang, H.; Li, Z.

    2017-12-01

    Flood control operation of multi-reservoir systems such as parallel reservoirs and hybrid reservoirs often suffer from complex interactions and trade-off among tributaries and the mainstream. The optimization of such systems is computationally intensive due to nonlinear storage curves, numerous constraints and complex hydraulic connections. This paper aims to derive the optimal flood control operating rules based on the trade-off among tributaries and the mainstream using a new algorithm known as weighted non-dominated sorting genetic algorithm II (WNSGA II). WNSGA II could locate the Pareto frontier in non-dominated region efficiently due to the directed searching by weighted crowding distance, and the results are compared with those of conventional operating rules (COR) and single objective genetic algorithm (GA). Xijiang river basin in China is selected as a case study, with eight reservoirs and five flood control sections within four tributaries and the mainstream. Furthermore, the effects of inflow uncertainty have been assessed. Results indicate that: (1) WNSGA II could locate the non-dominated solutions faster and provide better Pareto frontier than the traditional non-dominated sorting genetic algorithm II (NSGA II) due to the weighted crowding distance; (2) WNSGA II outperforms COR and GA on flood control in the whole basin; (3) The multi-objective operating rules from WNSGA II deal with the inflow uncertainties better than COR. Therefore, the WNSGA II can be used to derive stable operating rules for large-scale reservoir systems effectively and efficiently.

  14. RCC-F: Design and construction rules for PWR fire protection systems

    International Nuclear Information System (INIS)

    2013-01-01

    The RCC-F code defines the rules for designing, building and installing the fire protection systems used to manage the nuclear hazards inherent in the outbreak of a fire inside the facility and thereby control the fundamental nuclear functions. The code provides fire protection recommendations in terms of: the industrial risk (loss of assets and/or operation), personnel safety, the environment. The code is divided into five main sections: generalities, design safety principles, fire protection design bases, construction provisions, rules for installing the fire protection components and equipment. The RCC-F code is available as an ETC-F version specifically for EPR projects (European pressurized reactor). Contents of the 2013 edition of the ETC-F code: Volume A - Generalities: Structure of ETC-F general points, documentation (in progress), chapter (provision) quality assurance; Volume B - Design safety principles: design nuclear safety principles; Volume C - Fire protection design bases: fire protection design bases; Volume D - Construction provisions: construction provisions; Volume E - Installation rules for fire protection: rules for installing the fire protection, components and equipment

  15. Optimization of Simple Monetary Policy Rules on the Base of Estimated DSGE-model

    OpenAIRE

    Shulgin, A.

    2015-01-01

    Optimization of coefficients in monetary policy rules is performed on the base of the DSGE-model with two independent monetary policy instruments estimated on the Russian data. It was found that welfare maximizing policy rules lead to inadequate result and pro-cyclical monetary policy. Optimal coefficients in Taylor rule and exchange rate rule allow to decrease volatility estimated on Russian data of 2001-2012 by about 20%. The degree of exchange rate flexibility parameter was found to be low...

  16. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

    Science.gov (United States)

    Li, Yang; Li, Guoqing; Wang, Zhenhao

    2015-01-01

    In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

  17. Domain XML semantic integration based on extraction rules and ontology mapping

    Directory of Open Access Journals (Sweden)

    Huayu LI

    2016-08-01

    Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

  18. A Rule-Based Data Transfer Protocol for On-Demand Data Exchange in Vehicular Environment

    Directory of Open Access Journals (Sweden)

    Liao Hsien-Chou

    2009-01-01

    Full Text Available The purpose of Intelligent Transport System (ITS is mainly to increase the driving safety and efficiency. Data exchange is an important way to achieve the purpose. An on-demand data exchange is especially useful to assist a driver avoiding some emergent events. In order to handle the data exchange under dynamic situations, a rule-based data transfer protocol is proposed in this paper. A set of rules is designed according to the principle of request-forward-reply (RFR. That is, they are used to determine the timing of data broadcasting, forwarding, and replying automatically. Two typical situations are used to demonstrate the operation of rules. One is the front view of a driver occluded by other vehicles. The other is the traffic jam. The proposed protocol is flexible and extensible for unforeseen situations. Three simulation tools were also implemented to demonstrate the feasibility of the protocol and measure the network transmission under high density of vehicles. The simulation results show that the rule-based protocol is efficient on data exchange to increase the driving safety.

  19. A Novel Rules Based Approach for Estimating Software Birthmark

    Science.gov (United States)

    Binti Alias, Norma; Anwar, Sajid

    2015-01-01

    Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark. PMID:25945363

  20. On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses.

    Science.gov (United States)

    Song, Tao; Xu, Jinbang; Pan, Linqiang

    2015-12-01

    Spiking neural P systems with rules on synapses are a new variant of spiking neural P systems. In the systems, the neuron contains only spikes, while the spiking/forgetting rules are moved on the synapses. It was obtained that such system with 30 neurons (using extended spiking rules) or with 39 neurons (using standard spiking rules) is Turing universal. In this work, this number is improved to 6. Specifically, we construct a Turing universal spiking neural P system with rules on synapses having 6 neurons, which can generate any set of Turing computable natural numbers. As well, it is obtained that spiking neural P system with rules on synapses having less than two neurons are not Turing universal: i) such systems having one neuron can characterize the family of finite sets of natural numbers; ii) the family of sets of numbers generated by the systems having two neurons is included in the family of semi-linear sets of natural numbers.

  1. Agent-oriented enterprise modeling based on business rules

    NARCIS (Netherlands)

    Taveter, K.; Wagner, G.R.; Kunii, H.S.; Jajodia, S.; Solvberg, A.

    2001-01-01

    Business rules are statements that express (certain parts of) a business policy, defining business terms and defining or constraining the operations of an enterprise, in a declarative manner. Since these rules define and constrain the interaction among business agents in the course of business

  2. Phases, phase equilibria, and phase rules in low-dimensional systems

    International Nuclear Information System (INIS)

    Frolov, T.; Mishin, Y.

    2015-01-01

    We present a unified approach to thermodynamic description of one, two, and three dimensional phases and phase transformations among them. The approach is based on a rigorous definition of a phase applicable to thermodynamic systems of any dimensionality. Within this approach, the same thermodynamic formalism can be applied for the description of phase transformations in bulk systems, interfaces, and line defects separating interface phases. For both lines and interfaces, we rigorously derive an adsorption equation, the phase coexistence equations, and other thermodynamic relations expressed in terms of generalized line and interface excess quantities. As a generalization of the Gibbs phase rule for bulk phases, we derive phase rules for lines and interfaces and predict the maximum number of phases than may coexist in systems of the respective dimensionality

  3. Symmetry in quantum system theory: Rules for quantum architecture design

    Energy Technology Data Exchange (ETDEWEB)

    Schulte-Herbrueggen, Thomas; Sander, Uwe [Technical University of Munich, Garching (Germany). Dept. Chem.

    2010-07-01

    We investigate universality in the sense of controllability and observability, of multi-qubit systems in architectures of various symmetries of coupling type and topology. By determining the respective dynamic system Lie algebras, explicit reachability sets under symmetry constraints are provided. Thus for a given (possibly symmetric) experimental coupling architecture several decision problems can be solved in a unified way: (i) can a target Hamiltonian be simulated? (ii) can a target gate be synthesised? (iii) to which extent is the system observable by a given set of detection operators? and, as a special case of the latter, (iv) can an underlying system Hamiltonian be identified with a given set of detection operators? Finally, in turn, the absence of symmetry provides a convenient necessary condition for full controllability. Though often easier to assess than the well-established Lie-algebra rank condition, this is not sufficient unless the candidate dynamic simple Lie algebra can be pre-identified uniquely. Thus for architectures with various Ising and Heisenberg coupling types we give design rules sufficient to ensure full controllability. In view of follow-up studies, we relate the unification of necessary and sufficient conditions for universality to filtering simple Lie subalgebras of su(N) comprising classical and exceptional types.

  4. Rule-Based and Case-Based Reasoning in Housing Prices

    OpenAIRE

    Gabrielle Gayer; Itzhak Gilboa; Offer Lieberman

    2004-01-01

    People reason about real-estate prices both in terms of general rules and in terms of analogies to similar cases. We propose to empirically test which mode of reasoning fits the data better. To this end, we develop the statistical techniques required for the estimation of the case-based model. It is hypothesized that case-based reasoning will have relatively more explanatory power in databases of rental apartments, whereas rule-based reasoning will have a relative advantage in sales data. We ...

  5. Under What Conditions Do Rules-Based and Capability-Based Management Modes Dominate?

    Directory of Open Access Journals (Sweden)

    Lukas Michel

    2018-04-01

    Full Text Available Despite real changes in the work place and the negative consequences of prevailing hierarchical structures with rigid management systems, little attention has yet been paid to shifting management modes to accommodate the dynamics of the external environment, particularly when a firm’s operating environment demands a high degree of flexibility. Building on the resource-based view as a basis for competitive advantage, we posit that differences in the stability of an organization’s environment and the degree of managerial control explain variations in the management mode used in firms. Unlike other studies which mainly focus on either the dynamics of the external environment or management control, we have developed a theoretical model combining both streams of research, in a context frame to describe under what conditions firms engage in rules-based, change-based, engagement-based and capability-based management modes. To test our theoretical framework, we conducted a survey with 54 firms in various industries and nations on how their organizations cope with a dynamic environment and what management style they used in response. Our study reveals that the appropriate mode can be determined by analyzing purpose, motivation, knowledge and information, as well as the degree of complexity, volatility and uncertainty the firm is exposed to. With our framework, we attempt to advance the understanding of when organizations should adapt their management style to the changing business environment.

  6. Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore

    Directory of Open Access Journals (Sweden)

    Jan Huwald

    2013-07-01

    Full Text Available A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models.

  7. CERN’s Computing rules updated to include policy for control systems

    CERN Multimedia

    IT Department

    2008-01-01

    The use of CERN’s computing facilities is governed by rules defined in Operational Circular No. 5 and its subsidiary rules of use. These rules are available from the web site http://cern.ch/ComputingRules. Please note that the subsidiary rules for Internet/Network use have been updated to include a requirement that control systems comply with the CNIC(Computing and Network Infrastructure for Control) Security Policy. The security policy for control systems, which was approved earlier this year, can be accessed at https://edms.cern.ch/document/584092 IT Department

  8. 75 FR 36089 - Payment System Risk Policy; Daylight Overdraft Posting Rules

    Science.gov (United States)

    2010-06-24

    ... FEDERAL RESERVE SYSTEM [OP-1385] Payment System Risk Policy; Daylight Overdraft Posting Rules... Payment System Risk Policy, the Board is announcing posting rules for a new same-day automated clearing... Kirkpatrick, Senior Financial Services Analyst, Payment System Risk (202-452-2796), or Jennifer Davidson...

  9. Spatial snowdrift game in heterogeneous agent systems with co-evolutionary strategies and updating rules

    International Nuclear Information System (INIS)

    Xia Hai-Jiang; Li Ping-Ping; Ke Jian-Hong; Lin Zhen-Quan

    2015-01-01

    We propose an evolutionary snowdrift game model for heterogeneous systems with two types of agents, in which the inner-directed agents adopt the memory-based updating rule while the copycat-like ones take the unconditional imitation rule; moreover, each agent can change his type to adopt another updating rule once the number he sequentially loses the game at is beyond his upper limit of tolerance. The cooperative behaviors of such heterogeneous systems are then investigated by Monte Carlo simulations. The numerical results show the equilibrium cooperation frequency and composition as functions of the cost-to-benefit ratio r are both of plateau structures with discontinuous steplike jumps, and the number of plateaux varies non-monotonically with the upper limit of tolerance ν T as well as the initial composition of agents f a0 . Besides, the quantities of the cooperation frequency and composition are dependent crucially on the system parameters including ν T , f a0 , and r. One intriguing observation is that when the upper limit of tolerance is small, the cooperation frequency will be abnormally enhanced with the increase of the cost-to-benefit ratio in the range of 0 < r < 1/4. We then probe into the relative cooperation frequencies of either type of agents, which are also of plateau structures dependent on the system parameters. Our results may be helpful to understand the cooperative behaviors of heterogenous agent systems. (paper)

  10. State Identification of Hoisting Motors Based on Association Rules for Quayside Container Crane

    Science.gov (United States)

    Li, Q. Z.; Gang, T.; Pan, H. Y.; Xiong, H.

    2017-07-01

    Quay container crane hoisting motor is a complex system, and the characteristics of long-term evolution and change of running status of there is a rule, and use it. Through association rules analysis, this paper introduced the similarity in association rules, and quay container crane hoisting motor status identification. Finally validated by an example, some rules change amplitude is small, regular monitoring, not easy to find, but it is precisely because of these small changes led to mechanical failure. Therefore, using the association rules change in monitoring the motor status has the very strong practical significance.

  11. Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications

    Science.gov (United States)

    Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy. PMID:24511304

  12. Classification based on pruning and double covered rule sets for the internet of things applications.

    Science.gov (United States)

    Li, Shasha; Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy.

  13. Heuristic simulation of nuclear systems on a supercomputer using the HAL-1987 general-purpose production-rule analysis system

    International Nuclear Information System (INIS)

    Ragheb, M.; Gvillo, D.; Makowitz, H.

    1987-01-01

    HAL-1987 is a general-purpose tool for the construction of production-rule analysis systems. It uses the rule-based paradigm from the part of artificial intelligence concerned with knowledge engineering. It uses backward-chaining and forward-chaining in an antecedent-consequent logic, and is programmed in Portable Standard Lisp (PSL). The inference engine is flexible and accommodates general additions and modifications to the knowledge base. The system is used in coupled symbolic-procedural programming adaptive methodologies for stochastic simulations. In Monte Carlo simulations of particle transport, the system considers the pre-processing of the input data to the simulation and adaptively controls the variance reduction process as the simulation progresses. This is accomplished through the use of a knowledge base of rules which encompass the user's expertise in the variance reduction process. It is also applied to the construction of model-based systems for monitoring, fault-diagnosis and crisis-alert in engineering devices, particularly in the field of nuclear reactor safety analysis

  14. Light-cone sum rules: A SCET-based formulation

    CERN Document Server

    De Fazio, F; Hurth, Tobias; Feldmann, Th.

    2007-01-01

    We describe the construction of light-cone sum rules (LCSRs) for exclusive $B$-meson decays into light energetic hadrons from correlation functions within soft-collinear effective theory (SCET). As an example, we consider the SCET sum rule for the $B \\to \\pi$ transition form factor at large recoil, including radiative corrections from hard-collinear loop diagrams at first order in the strong coupling constant.

  15. Transfer of Rule-Based Expertise through a Tutorial Dialogue

    Science.gov (United States)

    1979-09-01

    be causing the infection (.2) [RULE633]. {The student asks, "Does the patient have a fever ?") " FEBRILE MYCIN never needed to inquire about whether...remaining clauses, some we classified most as restrictions, and the one or two that remained constituted the key factor(s) of the rule. The " petechial ...Infection is bacterial, KEY-FACTORt 4) Petechial is one of the types of rash which the patient has, RESTRICTIONS 5) Purpuric is not one of the types

  16. A General Attribute and Rule Based Role-Based Access Control Model

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Growing numbers of users and many access control policies which involve many different resource attributes in service-oriented environments bring various problems in protecting resource. This paper analyzes the relationships of resource attributes to user attributes in all policies, and propose a general attribute and rule based role-based access control(GAR-RBAC) model to meet the security needs. The model can dynamically assign users to roles via rules to meet the need of growing numbers of users. These rules use different attribute expression and permission as a part of authorization constraints, and are defined by analyzing relations of resource attributes to user attributes in many access policies that are defined by the enterprise. The model is a general access control model, and can support many access control policies, and also can be used to wider application for service. The paper also describes how to use the GAR-RBAC model in Web service environments.

  17. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

    Science.gov (United States)

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

    Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

  18. Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification

    Directory of Open Access Journals (Sweden)

    Mokhamad Iklil Mustofa

    2017-05-01

    Full Text Available The scarcity of fuel oil in Indonesia often occurs due to delays in delivery caused by natural factors or transportation constraints. Theaim of this  research is to develop systems of fuel distribution monitoring online and realtime using rule base reasoning method and radio frequency identification technology. The rule-based reasoning method is used as a rule-based reasoning model used for monitoring distribution and determine rule-based safety stock. The monitoring system program is run with a web-based computer application. Radio frequency identification technology is used by utilizing radio waves as an media identification. This technology is used as a system of tracking and gathering information from objects automatically. The research data uses data of delayed distribution of fuel from fuel terminal to consumer. The monitoring technique uses the time of departure, the estimated time to arrive, the route / route passed by a fuel tanker attached to the radio frequency Identification tag. This monitoring system is carried out by the radio frequency identification reader connected online at any gas station or specified position that has been designed with study case in Semarang. The results of the research covering  the status of rule based reasoning that sends status, that is timely and appropriate paths, timely and truncated pathways, late and on track, late and cut off, and tank lost. The monitoring system is also used in determining the safety stock warehouse, with the safety stock value determined based on the condition of the stock warehouse rules.

  19. Mode Selection Rule for Three-Delay Systems

    Science.gov (United States)

    Takahashi, Kin'ya; Kobayashi, Taizo

    2017-12-01

    We study the mode selection rule for a three-delay system to determine which oscillation mode is first excited by the Hopf bifurcation with increasing control parameter. We use linear stability analysis to detect an oscillating mode excited by the first bifurcation. There are two conditions, relevant and irrelevant conditions, determined by the ratios of three delay times, t1, t2, and tf, where tf is fixed and t1 and t2 are set as 0 < t1 < tf and 0 < t2 < tf. In a neighborhood of the relevant condition defined such that both t1/tf = n1/m1 and t2/tf = n2/m2 are ratios of odd to odd, oscillations nearly equal to the \\tilde{m}th-harmonic mode are excited, where \\tilde{m} is the least common multiple of m1 and m2. In the parameter space (t1,t2), there are irrelevant lines each of which is determined by a rational dependence of t1, t2, and tf, and does not allow any relevant condition. Extremely high order modes are observed along both sides of the irrelevant line. In particular, the line t2 = tf - t1, i.e., a diagonal with a slope of -1, shows the strongest irrelevancy.

  20. Moving from Rule-based to Principle-based in Public Sector: Preparers' Perspective

    OpenAIRE

    Roshayani Arshad; Normah Omar; Siti Fatimah Awang

    2013-01-01

    The move from cash accounting to accrual accounting, or rule-based to principle-based accounting, by many governments is part of an ongoing efforts in promoting a more business-like and performance-focused public sector. Using questionnaire responses from preparers of financial statements of public universities in Malaysia, this study examines the implementation challenges and benefits of principle-based accounting. Results from these responses suggest that most respondents perceived signific...

  1. Application of refractive index mixing rules in binary systems of ...

    Indian Academy of Sciences (India)

    Unknown

    expressed in terms of average percentage deviation. The performance ... of these mixing rules is their inability to account for changes in volume and refractivity ..... symmetrical shape and it proposes volume additivity which is the reason for the.

  2. Optimization of decision rules based on dynamic programming approach

    KAUST Repository

    Zielosko, Beata

    2014-01-14

    This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.

  3. Rule-based conversion of closely-related languages: a Dutch-to-Afrikaans convertor

    CSIR Research Space (South Africa)

    Van Huyssteen, GB

    2009-11-01

    Full Text Available and performance of a rule-based Dutch-to-Afrikaans converter, with the aim to transform Dutch text so that it looks more like an Afrikaans text (even though it might not even be a good Dutch translation). The rules we used is based on systematic orthographic...

  4. Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection

    Directory of Open Access Journals (Sweden)

    Bloch Isabelle

    2007-01-01

    Full Text Available This paper describes a system for optical music recognition (OMR in case of monophonic typeset scores. After clarifying the difficulties specific to this domain, we propose appropriate solutions at both image analysis level and high-level interpretation. Thus, a recognition and segmentation method is designed, that allows dealing with common printing defects and numerous symbol interconnections. Then, musical rules are modeled and integrated, in order to make a consistent decision. This high-level interpretation step relies on the fuzzy sets and possibility framework, since it allows dealing with symbol variability, flexibility, and imprecision of music rules, and merging all these heterogeneous pieces of information. Other innovative features are the indication of potential errors and the possibility of applying learning procedures, in order to gain in robustness. Experiments conducted on a large data base show that the proposed method constitutes an interesting contribution to OMR.

  5. Opinion evolution based on cellular automata rules in small world networks

    Science.gov (United States)

    Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

    2010-03-01

    In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

  6. Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

    Science.gov (United States)

    Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

    2017-09-01

    This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

  7. Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks.

    Science.gov (United States)

    Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

    2016-07-07

    In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles.

  8. Transformation of Arden Syntax's medical logic modules into ArdenML for a business rules management system.

    Science.gov (United States)

    Jung, Chai Young; Choi, Jong-Ye; Jeong, Seong Jik; Cho, Kyunghee; Koo, Yong Duk; Bae, Jin Hee; Kim, Sukil

    2016-05-16

    Arden Syntax is a Health Level Seven International (HL7) standard language that is used for representing medical knowledge as logic statements. Arden Syntax Markup Language (ArdenML) is a new representation of Arden Syntax based on XML. Compilers are required to execute medical logic modules (MLMs) in the hospital environment. However, ArdenML may also replace the compiler. The purpose of this study is to demonstrate that MLMs, encoded in ArdenML, can be transformed into a commercial rule engine format through an XSLT stylesheet and made executable in a target system. The target rule engine selected was Blaze Advisor. We developed an XSLT stylesheet to transform MLMs in ArdenML into Structured Rules Language (SRL) in Blaze Advisor, through a comparison of syntax between the two languages. The stylesheet was then refined recursively, by building and applying rules collected from the billing and coding guidelines of the Korean health insurance service. Two nurse coders collected and verified the rules and two information technology (IT) specialists encoded the MLMs and built the XSLT stylesheet. Finally, the stylesheet was validated by importing the MLMs into Blaze Advisor and applying them to claims data. The language comparison revealed that Blaze Advisor requires the declaration of variables with explicit types. We used both integer and real numbers for numeric types in ArdenML. "IF∼THEN" statements and assignment statements in ArdenML become rules in Blaze Advisor. We designed an XSLT stylesheet to solve this issue. In addition, we maintained the order of rule execution in the transformed rules, and added two small programs to support variable declarations and action statements. A total of 1489 rules were reviewed during this study, of which 324 rules were collected. We removed duplicate rules and encoded 241 unique MLMs in ArdenML, which were successfully transformed into SRL and imported to Blaze Advisor via the XSLT stylesheet. When applied to 73

  9. A rule-based approach to model checking of UML state machines

    Science.gov (United States)

    Grobelna, Iwona; Grobelny, Michał; Stefanowicz, Łukasz

    2016-12-01

    In the paper a new approach to formal verification of control process specification expressed by means of UML state machines in version 2.x is proposed. In contrast to other approaches from the literature, we use the abstract and universal rule-based logical model suitable both for model checking (using the nuXmv model checker), but also for logical synthesis in form of rapid prototyping. Hence, a prototype implementation in hardware description language VHDL can be obtained that fully reflects the primary, already formally verified specification in form of UML state machines. Presented approach allows to increase the assurance that implemented system meets the user-defined requirements.

  10. An investigation of care-based vs. rule-based morality in frontotemporal dementia, Alzheimer's disease, and healthy controls.

    Science.gov (United States)

    Carr, Andrew R; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S; Mather, Michelle; Jimenez, Elvira E; Thompson, Paul; Mendez, Mario F

    2015-11-01

    Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer's disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. Published by Elsevier Ltd.

  11. Using fuzzy rule-based knowledge model for optimum plating conditions search

    Science.gov (United States)

    Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.

    2018-03-01

    The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.

  12. Maintenance rule: a system to guarantee maintenance effectiveness

    International Nuclear Information System (INIS)

    Torralbo, J.R.

    1995-01-01

    In the last few years, maintenance activities in nuclear plants have been given prime attention in view of their repercussion on the performance of such plants. One of the results of that attention is a new rule published in the U.S. known as M aintenance Rule . The paper describes the philosophy and main guidelines of the new regulation, and presents the procedure brought into action by the nuclear industry in Spain so to make their application contribute to a real improvement of safety and performance in nuclear plants. (Author)

  13. Probabilistic based design rules for intersystem LOCAS in ABWR piping

    International Nuclear Information System (INIS)

    Ware, A.G.; Wesley, D.A.

    1993-01-01

    A methodology has been developed for probability-based standards for low-pressure piping systems that are attached to the reactor coolant loops of advanced light water reactors (ALWRs) which could experience reactor coolant loop temperatures and pressures because of multiple isolation valve failures. This accident condition is called an intersystem loss-of-coolant accident (ISLOCA). The methodology was applied to various sizes of carbon and stainless steel piping designed to advanced boiling water reactor (ABWR) temperatures and pressures

  14. Rules of Origin: Conceptual Explorations and Lessons from the Generalized System of Preferences

    OpenAIRE

    Ujiie, Teruo

    2006-01-01

    Customs valuation, commodity classification system, and rules of origin are the three basic customs laws. Rules to determine a country of origin, or "nationality" of a country of production of goods, are called "rules of origin." They are widely used in international trade in the application of different tariffs, trade remedy measures, tariff quotas, and trade statistics. With the globalization of economic activities resulting in outsourcing of materials as well as the global proliferation of...

  15. Verification of business rules programs

    CERN Document Server

    Silva, Bruno Berstel-Da

    2013-01-01

    Rules represent a simplified means of programming, congruent with our understanding of human brain constructs. With the advent of business rules management systems, it has been possible to introduce rule-based programming to nonprogrammers, allowing them to map expert intent into code in applications such as fraud detection, financial transactions, healthcare, retail, and marketing. However, a remaining concern is the quality, safety, and reliability of the resulting programs.  This book is on business rules programs, that is, rule programs as handled in business rules management systems. Its

  16. Automated detection of pain from facial expressions: a rule-based approach using AAM

    Science.gov (United States)

    Chen, Zhanli; Ansari, Rashid; Wilkie, Diana J.

    2012-02-01

    In this paper, we examine the problem of using video analysis to assess pain, an important problem especially for critically ill, non-communicative patients, and people with dementia. We propose and evaluate an automated method to detect the presence of pain manifested in patient videos using a unique and large collection of cancer patient videos captured in patient homes. The method is based on detecting pain-related facial action units defined in the Facial Action Coding System (FACS) that is widely used for objective assessment in pain analysis. In our research, a person-specific Active Appearance Model (AAM) based on Project-Out Inverse Compositional Method is trained for each patient individually for the modeling purpose. A flexible representation of the shape model is used in a rule-based method that is better suited than the more commonly used classifier-based methods for application to the cancer patient videos in which pain-related facial actions occur infrequently and more subtly. The rule-based method relies on the feature points that provide facial action cues and is extracted from the shape vertices of AAM, which have a natural correspondence to face muscular movement. In this paper, we investigate the detection of a commonly used set of pain-related action units in both the upper and lower face. Our detection results show good agreement with the results obtained by three trained FACS coders who independently reviewed and scored the action units in the cancer patient videos.

  17. Application of refractive index mixing rules in binary systems of ...

    Indian Academy of Sciences (India)

    ... entire mole fraction range of hexadecane and heptadecane at the three temperatures. Comparison of various mixing rules has been expressed in terms of average percentage deviation. The performance of the Lorentz- Lorenz and Heller relations is relatively better than that of the Weiner and Gladstone-Dale relations.

  18. Flavours of XChange, a Rule-Based Reactive Language for the (Semantic) Web

    OpenAIRE

    Bailey, James; Bry, François; Eckert, Michael; Patrânjan, Paula Lavinia

    2005-01-01

    This article introduces XChange, a rule-based reactive language for the Web. Stressing application scenarios, it first argues that high-level reactive languages are needed for bothWeb and SemanticWeb applications. Then, it discusses technologies and paradigms relevant to high-level reactive languages for the (Semantic) Web. Finally, it presents the Event-Condition-Action rules of XChange.

  19. A PROBABILITY BASED APPROACH FOR THE ALLOCATION OF PLAYER DRAFT SELECTIONS IN AUSTRALIAN RULES FOOTBALL

    Directory of Open Access Journals (Sweden)

    Anthony Bedford

    2006-12-01

    Full Text Available Australian Rules Football, governed by the Australian Football League (AFL is the most popular winter sport played in Australia. Like North American team based leagues such as the NFL, NBA and NHL, the AFL uses a draft system for rookie players to join a team's list. The existing method of allocating draft selections in the AFL is simply based on the reverse order of each team's finishing position for that season, with teams winning less than or equal to 5 regular season matches obtaining an additional early round priority draft pick. Much criticism has been levelled at the existing system since it rewards losing teams and does not encourage poorly performing teams to win matches once their season is effectively over. We propose a probability-based system that allocates a score based on teams that win 'unimportant' matches (akin to Carl Morris' definition of importance. We base the calculation of 'unimportance' on the likelihood of a team making the final eight following each round of the season. We then investigate a variety of approaches based on the 'unimportance' measure to derive a score for 'unimportant' and unlikely wins. We explore derivatives of this system, compare past draft picks with those obtained under our system, and discuss the attractiveness of teams knowing the draft reward for winning each match in a season

  20. Decision tables and rule engines in organ allocation systems for optimal transparency and flexibility.

    Science.gov (United States)

    Schaafsma, Murk; van der Deijl, Wilfred; Smits, Jacqueline M; Rahmel, Axel O; de Vries Robbé, Pieter F; Hoitsma, Andries J

    2011-05-01

    Organ allocation systems have become complex and difficult to comprehend. We introduced decision tables to specify the rules of allocation systems for different organs. A rule engine with decision tables as input was tested for the Kidney Allocation System (ETKAS). We compared this rule engine with the currently used ETKAS by running 11,000 historical match runs and by running the rule engine in parallel with the ETKAS on our allocation system. Decision tables were easy to implement and successful in verifying correctness, completeness, and consistency. The outcomes of the 11,000 historical matches in the rule engine and the ETKAS were exactly the same. Running the rule engine simultaneously in parallel and in real time with the ETKAS also produced no differences. Specifying organ allocation rules in decision tables is already a great step forward in enhancing the clarity of the systems. Yet, using these tables as rule engine input for matches optimizes the flexibility, simplicity and clarity of the whole process, from specification to the performed matches, and in addition this new method allows well controlled simulations. © 2011 The Authors. Transplant International © 2011 European Society for Organ Transplantation.

  1. Expert system based radionuclide identification

    International Nuclear Information System (INIS)

    Aarnio, P.A.; Ala-Heikkil, J.J.; Hakulinen, T.T.; Nikkinen, M.T.

    1998-01-01

    An expert system coupled with the gamma spectrum analysis system SAMPO has been developed for automating the qualitative identification of radionuclides as well as for determining the quantitative parameters of the spectrum components. The program is written in C-language and runs in various environments ranging from PCs to UNIX workstations. The expert system utilizes a complete gamma library with over 2600 nuclides and 80,000 lines, and a rule base of about fifty criteria including energies, relative peak intensities, genesis modes, half lives, parent-daughter relationships, etc. The rule base is furthermore extensible by the user. This is not an original contribution but a somewhat updated version of papers and reports previously published elsewhere. (author)

  2. Ketamine alters lateral prefrontal oscillations in a rule-based working memory task.

    Science.gov (United States)

    Ma, Liya; Skoblenick, Kevin; Johnston, Kevin; Everling, Stefan

    2018-02-02

    Acute administration of N-methyl-D-aspartate receptor (NMDAR) antagonists in healthy humans and animals produces working memory deficits similar to those observed in schizophrenia. However, it is unclear whether they also lead to altered low-frequency (rule-based prosaccade and antisaccade working memory task, both before and after systemic injections of a subanesthetic dose (delay periods and inter-trial intervals. It also increased task-related alpha-band activities, likely reflecting compromised attention. Beta-band oscillations may be especially relevant to working memory processes, as stronger beta power weakly but significantly predicted shorter saccadic reaction time. Also in beta band, ketamine reduced the performance-related oscillation as well as the rule information encoded in the spectral power. Ketamine also reduced rule information in the spike-field phase consistency in almost all frequencies up to 60Hz. Our findings support NMDAR antagonists in non-human primates as a meaningful model for altered neural oscillations and synchrony, which reflect a disorganized network underlying the working memory deficits in schizophrenia. SIGNIFICANCE STATEMENT Low doses of ketamine-an NMDA receptor blocker-produce working memory deficits similar to those observed in schizophrenia. In the LPFC, a key brain region for working memory, we found that ketamine altered neural oscillatory activities in similar ways that differentiate schizophrenic patients and healthy subjects, during both task and non-task periods. Ketamine induced stronger gamma (30-60Hz) and weaker beta (13-30Hz) oscillations, reflecting local hyperactivity and reduced long-range communications. Furthermore, ketamine reduced performance-related oscillatory activities, as well as the rule information encoded in the oscillations and in the synchrony between single cell activities and oscillations. The ketamine model helps link the molecular and cellular basis of neural oscillatory changes to the working

  3. PRINCIPLES- AND RULES-BASED ACCOUNTING DEBATE. IMPLICATIONS FOR AN EMERGENT COUNTRY

    Directory of Open Access Journals (Sweden)

    Deaconu Adela

    2011-07-01

    Full Text Available By a qualitative analysis, this research observes whether a principles-based system or a mixed version of it with the rules-based system, applied in Romania - an emergent country - is appropriate taking into account the mentalities, the traditions, and other cultural elements that were typical of a rules-based system. We support the statement that, even if certain contextual variables are common to other developed countries, their environments significantly differ. To be effective, financial reporting must reflect the firm's context in which it is functioning. The research has a deductive approach based on the analysis of the cultural factors and their influence in the last years. For Romania it is argue a lower accounting professionalism associated with a low level of ambiguity tolerance. For the stage analysed in this study (after the year 2005 the professional reasoning - a proxy for the accounting professional behaviour - took into consideration the fiscal and legal requirements rather than the accounting principles and judgments. The research suggest that the Romanian accounting practice and the professionals are not fully prepared for a principles-based system environment, associated with the ability to find undisclosed events, facing ambiguity, identifying inferred relationships and using intuition, respectively working with uncertainty. We therefore reach the conclusion that in Romania institutional amendments affecting the professional expertise would be needed. The accounting regulations must be chosen with great caution and they must answer and/ or be adjusted, even if the process would be delayed, to national values, behaviour of companies and individual expertise and beliefs. Secondly, the benefits of applying accounting reasoning in this country may be enhanced through a better understanding of their content and through practical exercise. Here regulatory bodies may intervene for organizing professional training programs and acting

  4. Prediction on carbon dioxide emissions based on fuzzy rules

    Science.gov (United States)

    Pauzi, Herrini; Abdullah, Lazim

    2014-06-01

    There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

  5. Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

    Science.gov (United States)

    Opitz, Bertram; Hofmann, Juliane

    2015-03-01

    A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule testing. Crucially, the latter is facilitated by performance feedback that encourages explicit hypothesis testing. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. 75 FR 11002 - Hazardous Waste Management System; Identification and Listing of Hazardous Waste; Final Rule

    Science.gov (United States)

    2010-03-10

    ... Waste Management System; Identification and Listing of Hazardous Waste; Final Rule AGENCY: Environmental... and specific types of management of the petitioned waste, the quantities of waste generated, and waste... wastes. This final rule responds to a petition submitted by Valero to delist F037 waste. The F037 waste...

  7. 75 FR 4101 - Enterprise Income Verification (EIV) System User Access Authorization Form and Rules of Behavior...

    Science.gov (United States)

    2010-01-26

    ... DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT [Docket No. FR-5376-N-05] Enterprise Income Verification (EIV) System User Access Authorization Form and Rules of Behavior and User Agreement AGENCY... Access, Authorization Form and Rules Of Behavior and User Agreement. OMB Approval Number: 2577-New. Form...

  8. Critiquing the Transatlantic Trade and Investment Partnership (TTIP) : Systemic Consequences for Global Governance and the Rule of Law

    NARCIS (Netherlands)

    Larik, J.E.

    2016-01-01

    Considering the implications of the Transatlantic Trade and Investment Partnership (TTIP) for the architecture of global (economic) governance, including the international rule of law, the article addresses some of the most pertinent systemic consequences TTIP is likely to produce, based on the

  9. The research on business rules classification and specification methods

    OpenAIRE

    Baltrušaitis, Egidijus

    2005-01-01

    The work is based on the research of business rules classification and specification methods. The basics of business rules approach are discussed. The most common business rules classification and modeling methods are analyzed. Business rules modeling techniques and tools for supporting them in the information systems are presented. Basing on the analysis results business rules classification method is proposed. Templates for every business rule type are presented. Business rules structuring ...

  10. The Design and Implementation of the Ariel Active Database Rule System

    Science.gov (United States)

    1991-10-01

    but only as a main-memory prototype. The POSTGRES rule system (PRS) [SHP88, SRH90] and the Starburst rule system (SRS) [WCL91, HCL+90] have been...query language of POSTGRES for specifying data definition commands, queries and updates [SRH90]. POSTQUEL commands retrieve, append, delete, and replace...placed on an arbitrary attribute (e.g., one without an index) ( POSTGRES rule system [SHP88, SHP89, SR1I90], HiPAC [C+891, DIPS [SLR89], Alert [SPAM91

  11. Collaborative Working e-Learning Environments Supported by Rule-Based e-Tutor

    Directory of Open Access Journals (Sweden)

    Salaheddin Odeh

    2007-10-01

    Full Text Available Collaborative working environments for distance education sets a goal of convenience and an adaptation into our technologically advanced societies. To achieve this revolutionary new way of learning, environments must allow the different participants to communicate and coordinate with each other in a productive manner. Productivity and efficiency is obtained through synchronized communication between the different coordinating partners, which means that multiple users can execute an experiment simultaneously. Within this process, coordination can be accomplished by voice communication and chat tools. In recent times, multi-user environments have been successfully applied in many applications such as air traffic control systems, team-oriented military systems, chat text tools, and multi-player games. Thus, understanding the ideas and the techniques behind these systems can be of great significance regarding the contribution of newer ideas to collaborative working e-learning environments. However, many problems still exist in distance learning and tele-education, such as not finding the proper assistance while performing the remote experiment. Therefore, the students become overwhelmed and the experiment will fail. In this paper, we are going to discuss a solution that enables students to obtain an automated help by either a human tutor or a rule-based e-tutor (embedded rule-based system for the purpose of student support in complex remote experimentative environments. The technical implementation of the system can be realized by using the powerful Microsoft .NET, which offers a complete integrated developmental environment (IDE with a wide collection of products and technologies. Once the system is developed, groups of students are independently able to coordinate and to execute the experiment at any time and from any place, organizing the work between them positively.

  12. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    International Nuclear Information System (INIS)

    Wang, M; Hu, N Q; Qin, G J

    2011-01-01

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  13. Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

    KAUST Repository

    Delimata, Paweł; Marszał-Paszek, Barbara; Moshkov, Mikhail; Paszek, Piotr; Skowron, Andrzej; Suraj, Zbigniew

    2010-01-01

    the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory

  14. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Wang, M; Hu, N Q; Qin, G J, E-mail: hnq@nudt.edu.cn, E-mail: wm198063@yahoo.com.cn [School of Mechatronic Engineering and Automation, National University of Defense Technology, ChangSha, Hunan, 410073 (China)

    2011-07-19

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  15. Design and performance of a rule-based controller in a naturally ventilated room

    OpenAIRE

    Marjanovic-Halburd, Ljiljana; Angelov, P.; Eftekhari, M. M.

    2003-01-01

    This paper reflects the final phase of the EPSRC project, and the PhD work of Marjanovic, on rule-based control in naturally ventilated buildings. Marjanovic is the second author. Eftekhari was her PhD supervisor.

  16. Change-Point Detection Method for Clinical Decision Support System Rule Monitoring.

    Science.gov (United States)

    Liu, Siqi; Wright, Adam; Hauskrecht, Milos

    2017-06-01

    A clinical decision support system (CDSS) and its components can malfunction due to various reasons. Monitoring the system and detecting its malfunctions can help one to avoid any potential mistakes and associated costs. In this paper, we investigate the problem of detecting changes in the CDSS operation, in particular its monitoring and alerting subsystem, by monitoring its rule firing counts. The detection should be performed online, that is whenever a new datum arrives, we want to have a score indicating how likely there is a change in the system. We develop a new method based on Seasonal-Trend decomposition and likelihood ratio statistics to detect the changes. Experiments on real and simulated data show that our method has a lower delay in detection compared with existing change-point detection methods.

  17. Applicability of creep damage rules to a nickel-base heat-resistant alloy Hastelloy XR

    International Nuclear Information System (INIS)

    Tsuji, Hirokazu; Nakajima, Najime; Tanabe, Tatsuhiko; Nakasone, Yuji

    1992-01-01

    A series of constant load and temperature creep rupture tests and varying load and/or temperature creep rupture tests was carried out on a nickel-base heat-resistant alloy Hastelloy XR, which was developed for applications in the High-Temperature Engineering Test Reactor, at temperatures ranging from 850 to 1000deg C in order to examine the applicability of the conventional creep damage rules, i.e., the life fraction, the strain fraction and their mixed rules. The life fraction rule showed the best applicability of these three criteria. The good applicability of the rule was considered to result from the fact that the creep strength of Hastelloy XR was not strongly affected by the change of the chemical composition and/or the microstructure during exposure to the high-temperature simulated HTGR helium environment. In conclusion the life fraction rule is applicable in engineering design of high-temperature components made of Hastelloy XR. (orig.)

  18. Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices

    OpenAIRE

    Lim, Suhwan; Bae, Jong-Ho; Eum, Jai-Ho; Lee, Sungtae; Kim, Chul-Heung; Kwon, Dongseok; Park, Byung-Gook; Lee, Jong-Ho

    2017-01-01

    In this paper, we propose a learning rule based on a back-propagation (BP) algorithm that can be applied to a hardware-based deep neural network (HW-DNN) using electronic devices that exhibit discrete and limited conductance characteristics. This adaptive learning rule, which enables forward, backward propagation, as well as weight updates in hardware, is helpful during the implementation of power-efficient and high-speed deep neural networks. In simulations using a three-layer perceptron net...

  19. Reservoir adaptive operating rules based on both of historical streamflow and future projections

    Science.gov (United States)

    Zhang, Wei; Liu, Pan; Wang, Hao; Chen, Jie; Lei, Xiaohui; Feng, Maoyuan

    2017-10-01

    Climate change is affecting hydrological variables and consequently is impacting water resources management. Historical strategies are no longer applicable under climate change. Therefore, adaptive management, especially adaptive operating rules for reservoirs, has been developed to mitigate the possible adverse effects of climate change. However, to date, adaptive operating rules are generally based on future projections involving uncertainties under climate change, yet ignoring historical information. To address this, we propose an approach for deriving adaptive operating rules considering both historical information and future projections, namely historical and future operating rules (HAFOR). A robustness index was developed by comparing benefits from HAFOR with benefits from conventional operating rules (COR). For both historical and future streamflow series, maximizations of both average benefits and the robustness index were employed as objectives, and four trade-offs were implemented to solve the multi-objective problem. Based on the integrated objective, the simulation-based optimization method was used to optimize the parameters of HAFOR. Using the Dongwushi Reservoir in China as a case study, HAFOR was demonstrated to be an effective and robust method for developing adaptive operating rules under the uncertain changing environment. Compared with historical or projected future operating rules (HOR or FPOR), HAFOR can reduce the uncertainty and increase the robustness for future projections, especially regarding results of reservoir releases and volumes. HAFOR, therefore, facilitates adaptive management in the context that climate change is difficult to predict accurately.

  20. Testing the performance of technical trading rules in the Chinese markets based on superior predictive test

    Science.gov (United States)

    Wang, Shan; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing

    2015-12-01

    Technical trading rules have a long history of being used by practitioners in financial markets. The profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousand traditional technical trading rules on the Shanghai Securities Composite Index (SSCI) from May 21, 1992 through June 30, 2013 and China Securities Index 300 (CSI 300) from April 8, 2005 through June 30, 2013 to check whether an effective trading strategy could be found by using the performance measurements based on the return and Sharpe ratio. To correct for the influence of the data-snooping effect, we adopt the Superior Predictive Ability test to evaluate if there exists a trading rule that can significantly outperform the benchmark. The result shows that for SSCI, technical trading rules offer significant profitability, while for CSI 300, this ability is lost. We further partition the SSCI into two sub-series and find that the efficiency of technical trading in sub-series, which have exactly the same spanning period as that of CSI 300, is severely weakened. By testing the trading rules on both indexes with a five-year moving window, we find that during the financial bubble from 2005 to 2007, the effectiveness of technical trading rules is greatly improved. This is consistent with the predictive ability of technical trading rules which appears when the market is less efficient.

  1. Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis

    International Nuclear Information System (INIS)

    Li Qiang; Doi Kunio

    2006-01-01

    Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists detect various lesions in medical images. In CAD schemes, classifiers play a key role in achieving a high lesion detection rate and a low false-positive rate. Although many popular classifiers such as linear discriminant analysis and artificial neural networks have been employed in CAD schemes for reduction of false positives, a rule-based classifier has probably been the simplest and most frequently used one since the early days of development of various CAD schemes. However, with existing rule-based classifiers, there are major disadvantages that significantly reduce their practicality and credibility. The disadvantages include manual design, poor reproducibility, poor evaluation methods such as resubstitution, and a large overtraining effect. An automated rule-based classifier with a minimized overtraining effect can overcome or significantly reduce the extent of the above-mentioned disadvantages. In this study, we developed an 'optimal' method for the selection of cutoff thresholds and a fully automated rule-based classifier. Experimental results performed with Monte Carlo simulation and a real lung nodule CT data set demonstrated that the automated threshold selection method can completely eliminate overtraining effect in the procedure of cutoff threshold selection, and thus can minimize overall overtraining effect in the constructed rule-based classifier. We believe that this threshold selection method is very useful in the construction of automated rule-based classifiers with minimized overtraining effect

  2. Context-Based Tourism Information Filtering with a Semantic Rule Engine

    Science.gov (United States)

    Lamsfus, Carlos; Martin, David; Alzua-Sorzabal, Aurkene; López-de-Ipiña, Diego; Torres-Manzanera, Emilio

    2012-01-01

    This paper presents the CONCERT framework, a push/filter information consumption paradigm, based on a rule-based semantic contextual information system for tourism. CONCERT suggests a specific insight of the notion of context from a human mobility perspective. It focuses on the particular characteristics and requirements of travellers and addresses the drawbacks found in other approaches. Additionally, CONCERT suggests the use of digital broadcasting as push communication technology, whereby tourism information is disseminated to mobile devices. This information is then automatically filtered by a network of ontologies and offered to tourists on the screen. The results obtained in the experiments carried out show evidence that the information disseminated through digital broadcasting can be manipulated by the network of ontologies, providing contextualized information that produces user satisfaction. PMID:22778584

  3. A two-stage stochastic rule-based model to determine pre-assembly buffer content

    Science.gov (United States)

    Gunay, Elif Elcin; Kula, Ufuk

    2018-01-01

    This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the altered sequence due to paint defects and upstream department constraints. First stage of the model decides the spare vehicle quantities, where the second stage model recovers the scrambled sequence respect to pre-defined rules. The problem is solved by sample average approximation (SAA) algorithm. We conduct a numerical study to compare the solutions of heuristic model with optimal ones and provide following insights: (i) as the mismatch between paint entrance and scheduled sequence decreases, the rule-based heuristic model recovers the scrambled sequence as good as the optimal resequencing model, (ii) the rule-based model is more sensitive to the mismatch between the paint entrance and scheduled sequences for recovering the scrambled sequence, (iii) as the defect rate increases, the difference in recovery effectiveness between rule-based heuristic and optimal solutions increases, (iv) as buffer capacity increases, the recovery effectiveness of the optimization model outperforms heuristic model, (v) as expected the rule-based model holds more inventory than the optimization model.

  4. Hedging Rules for Water Supply Reservoir Based on the Model of Simulation and Optimization

    Directory of Open Access Journals (Sweden)

    Yi Ji

    2016-06-01

    Full Text Available This study proposes a hedging rule model which is composed of a two-period reservior operation model considering the damage depth and hedging rule parameter optimization model. The former solves hedging rules based on a given poriod’s water supply weighting factor and carryover storage target, while the latter optimization model is used to optimize the weighting factor and carryover storage target based on the hedging rules. The coupling model gives the optimal poriod’s water supply weighting factor and carryover storage target to guide release. The conclusions achieved from this study as follows: (1 the water supply weighting factor and carryover storage target have a direct impact on the three elements of the hedging rule; (2 parameters can guide reservoirs to supply water reasonably after optimization of the simulation and optimization model; and (3 in order to verify the utility of the hedging rule, the Heiquan reservoir is used as a case study and particle swarm optimization algorithm with a simulation model is adopted for optimizing the parameter. The results show that the proposed hedging rule can improve the operation performances of the water supply reservoir.

  5. Optimizing Environmental Flow Operation Rules based on Explicit IHA Constraints

    Science.gov (United States)

    Dongnan, L.; Wan, W.; Zhao, J.

    2017-12-01

    Multi-objective operation of reservoirs are increasingly asked to consider the environmental flow to support ecosystem health. Indicators of Hydrologic Alteration (IHA) is widely used to describe environmental flow regimes, but few studies have explicitly formulated it into optimization models and thus is difficult to direct reservoir release. In an attempt to incorporate the benefit of environmental flow into economic achievement, a two-objective reservoir optimization model is developed and all 33 hydrologic parameters of IHA are explicitly formulated into constraints. The benefit of economic is defined by Hydropower Production (HP) while the benefit of environmental flow is transformed into Eco-Index (EI) that combined 5 of the 33 IHA parameters chosen by principal component analysis method. Five scenarios (A to E) with different constraints are tested and solved by nonlinear programming. The case study of Jing Hong reservoir, located in the upstream of Mekong basin, China, shows: 1. A Pareto frontier is formed by maximizing on only HP objective in scenario A and on only EI objective in scenario B. 2. Scenario D using IHA parameters as constraints obtains the optimal benefits of both economic and ecological. 3. A sensitive weight coefficient is found in scenario E, but the trade-offs between HP and EI objectives are not within the Pareto frontier. 4. When the fraction of reservoir utilizable capacity reaches 0.8, both HP and EI capture acceptable values. At last, to make this modelmore conveniently applied to everyday practice, a simplified operation rule curve is extracted.

  6. Coherent lower previsions in systems modelling: products and aggregation rules

    International Nuclear Information System (INIS)

    Cooman, Gert de; Troffaes, Matthias C.M.

    2004-01-01

    We discuss why coherent lower previsions provide a good uncertainty model for solving generic uncertainty problems involving possibly conflicting expert information. We study various ways of combining expert assessments on different domains, such as natural extension, independent natural extension and the type-I product, as well as on common domains, such as conjunction and disjunction. We provide each of these with a clear interpretation, and we study how they are related. Observing that in combining expert assessments no information is available about the order in which they should be combined, we suggest that the final result should be independent of the order of combination. The rules of combination we study here satisfy this requirement

  7. An alternative rule for determining demand and energy supply based in marginal cost optimization from interconnected hydrothermal systems, focalizing the individualized plants, applied to the interconnected system from South and Southeast regions of Brazil

    International Nuclear Information System (INIS)

    Souza Bond, P. de; Soares Filho, S.

    1989-01-01

    A methodology for determining optimal strategies of energy supply in the interconnected system from South and Southeast regions of Brazil is presented. The problem was modelled, having as principle the minimization of operation pluri annual cost. The dynamic restrictions of energy and peak flow, the dynamic configuration of hydrothermal park and the hydraulic operation restrictions are also considered. (C.G.C.). 7 refs, 3 tabs

  8. 78 FR 70046 - Payment System Risk Policy; Daylight Overdraft Posting Rules

    Science.gov (United States)

    2013-11-22

    ... FEDERAL RESERVE SYSTEM [Docket No. OP--1471] Payment System Risk Policy; Daylight Overdraft... Reserve Policy on Payment System Risk (PSR policy) to eliminate certain posting rules to conform with... Services Analyst (202- 452-2404), Division of Reserve Bank Operations and Payment Systems. For users of...

  9. Intelligent Flowcharting Developmental Approach to Legal Knowledge Based System

    Directory of Open Access Journals (Sweden)

    Nitin Balaji Bilgi

    2011-10-01

    Full Text Available The basic aim of this research, described in this paper is to develop a hybrid legal expert system/ knowledge based system, with specific reference to the transfer of property act, within the Indian legal system which is often in demand. In this paper the authors discuss an traditional approach to combining two types of reasoning methodologies, Rule Based Reasoning (RBR and Case Based Reasoning (CBR. In RBR module we have interpreted and implemented rules that occur in legal statutes of the Transfer of property act. In the CBR module we have an implementation to find the related cases. The VisiRule software made available by Logic Programming Associates is used in the development of RBR part this expert system. The authors have used java Net Beans for development of CBR. VisiRule is a decision charting tool, in which the rules are defined by a combination of graphical shapes and pieces of text, and produces rules.

  10. Expert system for web based collaborative CAE

    Science.gov (United States)

    Hou, Liang; Lin, Zusheng

    2006-11-01

    An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

  11. A rule-based verification and control framework in ATLAS Trigger-DAQ

    CERN Document Server

    Kazarov, A; Lehmann-Miotto, G; Sloper, J E; Ryabov, Yu; Computing In High Energy and Nuclear Physics

    2007-01-01

    In order to meet the requirements of ATLAS data taking, the ATLAS Trigger-DAQ system is composed of O(1000) of applications running on more than 2600 computers in a network. With such system size, s/w and h/w failures are quite often. To minimize system downtime, the Trigger-DAQ control system shall include advanced verification and diagnostics facilities. The operator should use tests and expertise of the TDAQ and detectors developers in order to diagnose and recover from errors, if possible automatically. The TDAQ control system is built as a distributed tree of controllers, where behavior of each controller is defined in a rule-based language allowing easy customization. The control system also includes verification framework which allow users to develop and configure tests for any component in the system with different levels of complexity. It can be used as a stand-alone test facility for a small detector installation, as part of the general TDAQ initialization procedure, and for diagnosing the problems ...

  12. Efficiency in Rule- vs. Plan-Based Movements Is Modulated by Action-Mode.

    Science.gov (United States)

    Scheib, Jean P P; Stoll, Sarah; Thürmer, J Lukas; Randerath, Jennifer

    2018-01-01

    The rule/plan motor cognition (RPMC) paradigm elicits visually indistinguishable motor outputs, resulting from either plan- or rule-based action-selection, using a combination of essentially interchangeable stimuli. Previous implementations of the RPMC paradigm have used pantomimed movements to compare plan- vs. rule-based action-selection. In the present work we attempt to determine the generalizability of previous RPMC findings to real object interaction by use of a grasp-to-rotate task. In the plan task, participants had to use prospective planning to achieve a comfortable post-handle rotation hand posture. The rule task used implementation intentions (if-then rules) leading to the same comfortable end-state. In Experiment A, we compare RPMC performance of 16 healthy participants in pantomime and real object conditions of the experiment, within-subjects. Higher processing efficiency of rule- vs. plan-based action-selection was supported by diffusion model analysis. Results show a significant response-time increase in the pantomime condition compared to the real object condition and a greater response-time advantage of rule-based vs. plan-based actions in the pantomime compared to the real object condition. In Experiment B, 24 healthy participants performed the real object RPMC task in a task switching vs. a blocked condition. Results indicate that plan-based action-selection leads to longer response-times and less efficient information processing than rule-based action-selection in line with previous RPMC findings derived from the pantomime action-mode. Particularly in the task switching mode, responses were faster in the rule compared to the plan task suggesting a modulating influence of cognitive load. Overall, results suggest an advantage of rule-based action-selection over plan-based action-selection; whereby differential mechanisms appear to be involved depending on the action-mode. We propose that cognitive load is a factor that modulates the advantageous

  13. Fuzzy rule-based landslide susceptibility mapping in Yığılca Forest District (Northwest of Turkey

    Directory of Open Access Journals (Sweden)

    Abdurrahim Aydın

    2016-07-01

    Full Text Available Landslide susceptibility map of Yığılca Forest District was formed based on developed fuzzy rules using GIS-based FuzzyCell software. An inventory of 315 landslides was updated through fieldworks after inventory map previously generated by the authors. Based on the landslide susceptibility mapping study previously made in the same area, for the comparison of two maps, same 8 landslide conditioning parameters were selected and then fuzzified for the landslide susceptibility mapping: land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature. Mamdani model was selected as fuzzy inference system. After fuzzy rules definition, Center of Area (COA was selected as defuzzification method in model. The output of developed model was normalized between 0 and 1, and then divided five classes such as very low, low, moderate, high, and very high. According to developed model based 8 conditioning parameters, landslide susceptibility in Yığılca Forest District varies between 32 and 67 (in range of 0-100 with 0.703 Area Under the Curve (AUC value. According to classified landslide susceptibility map, in Yığılca Forest District, 32.89% of the total area has high and very high susceptibility while 29.59% of the area has low and very low susceptibility and the rest located in moderate susceptibility. The result of developed fuzzy rule based model compared with previously generated landslide map with logistic regression (LR. According to comparison of the results of two studies, higher differences exist in terms of AUC value and dispersion of susceptibility classes. This is because fuzzy rule based model completely depends on how parameters are classified and fuzzified and also depends on how truly the expert composed the rules. Even so, GIS-based fuzzy applications provide very valuable facilities for reasoning, which makes it possible to take into account inaccuracies and uncertainties.

  14. Fusion of Thresholding Rules During Wavelet-Based Noisy Image Compression

    Directory of Open Access Journals (Sweden)

    Bekhtin Yury

    2016-01-01

    Full Text Available The new method for combining semisoft thresholding rules during wavelet-based data compression of images with multiplicative noise is suggested. The method chooses the best thresholding rule and the threshold value using the proposed criteria which provide the best nonlinear approximations and take into consideration errors of quantization. The results of computer modeling have shown that the suggested method provides relatively good image quality after restoration in the sense of some criteria such as PSNR, SSIM, etc.

  15. Rules-based analysis with JBoss Drools: adding intelligence to automation

    International Nuclear Information System (INIS)

    Ley, E. de; Jacobs, D.

    2012-01-01

    Rule engines are specialized software systems for applying conditional actions (if/then rules) on data. They are also known as 'production rule systems'. Rules engines are less-known as software technology than the traditional procedural, object-oriented, scripting or dynamic development languages. This is a pity, as their usage may offer an important enrichment to a development toolbox. JBoss Drools is an open-source rules engine that can easily be embedded in any Java application. Through an integration in our Passerelle process automation suite, we have been able to provide advanced solutions for intelligent process automation, complex event processing, system monitoring and alarming, automated repair etc. This platform has been proven for many years as an automated diagnosis and repair engine for Belgium's largest telecom provider, and it is being piloted at Synchrotron Soleil for device monitoring and alarming. After an introduction to rules engines in general and JBoss Drools in particular, we will present its integration in a solution platform, some important principles and a practical use case. (authors)

  16. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

    Directory of Open Access Journals (Sweden)

    Yang Li

    Full Text Available In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA methods, a new rule extraction method based on extreme learning machine (ELM and an improved Ant-miner (IAM algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

  17. Attribute Index and Uniform Design Based Multiobjective Association Rule Mining with Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Jie Zhang

    2013-01-01

    Full Text Available In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  18. Attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm.

    Science.gov (United States)

    Zhang, Jie; Wang, Yuping; Feng, Junhong

    2013-01-01

    In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  19. Access control system for two person rule at Rokkasho Reprocessing Plant

    International Nuclear Information System (INIS)

    Yanagisawa, Sawako; Ino, Munekazu; Yamada, Noriyuki; Oota, Hiroto; Iwasaki, Mitsuaki; Kodani, Yoshiki; Iwamoto, Tomonori

    2014-01-01

    Following the amendment and enforcement of Regulation of Reprocessing Activity on March 29th 2012, two person rule has become compulsory for the specific rooms to counter and prevent the sabotage or theft of nuclear materials by the insiders at reprocessing plant in Japan. The rooms will include those which contains cooling systems for decay heat removal from spent fuels and so on, scavenging systems to prevent the hydrogen accumulation, and those which contains nuclear material. To ensure the two person rule at Rokkasho Reprocessing Plant, JNFL has recently, after comprehensive study, introduced efficient and effective access control system for the rooms mentioned above. The system is composed of bio-attestation devices, surveillance cameras and electronic locks to establish access control system. This report outlines the access control system for two person rule and introduces the operation. (author)

  20. Evaluation of Rule-based Modularization in Model Transformation Languages illustrated with ATL

    NARCIS (Netherlands)

    Ivanov, Ivan; van den Berg, Klaas; Jouault, Frédéric

    This paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. Two scenarios are shown in which the modular units are identified on the base of the relations between source and target metamodels and on the base of generic transformation

  1. Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning.

    Science.gov (United States)

    Grimm, Lisa R; Maddox, W Todd

    2013-11-01

    Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.

  2. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2011-10-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and costsensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method;candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal parameters

  3. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2012-02-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and cost-sensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method; candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal

  4. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  5. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Science.gov (United States)

    Glaab, Enrico; Bacardit, Jaume; Garibaldi, Jonathan M; Krasnogor, Natalio

    2012-01-01

    Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  6. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

    Science.gov (United States)

    Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

    2016-07-01

    Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

  7. A Rule Based Approach to ISS Interior Volume Control and Layout

    Science.gov (United States)

    Peacock, Brian; Maida, Jim; Fitts, David; Dory, Jonathan

    2001-01-01

    Traditional human factors design involves the development of human factors requirements based on a desire to accommodate a certain percentage of the intended user population. As the product is developed human factors evaluation involves comparison between the resulting design and the specifications. Sometimes performance metrics are involved that allow leniency in the design requirements given that the human performance result is satisfactory. Clearly such approaches may work but they give rise to uncertainty and negotiation. An alternative approach is to adopt human factors design rules that articulate a range of each design continuum over which there are varying outcome expectations and interactions with other variables, including time. These rules are based on a consensus of human factors specialists, designers, managers and customers. The International Space Station faces exactly this challenge in interior volume control, which is based on anthropometric, performance and subjective preference criteria. This paper describes the traditional approach and then proposes a rule-based alternative. The proposed rules involve spatial, temporal and importance dimensions. If successful this rule-based concept could be applied to many traditional human factors design variables and could lead to a more effective and efficient contribution of human factors input to the design process.

  8. Rule-based category learning in children: the role of age and executive functioning.

    Directory of Open Access Journals (Sweden)

    Rahel Rabi

    Full Text Available Rule-based category learning was examined in 4-11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning.

  9. Agile Service Development: A Rule-Based Method Engineering Approach

    NARCIS (Netherlands)

    dr. Martijn Zoet; Stijn Hoppenbrouwers; Inge van de Weerd; Johan Versendaal

    2011-01-01

    Agile software development has evolved into an increasingly mature software development approach and has been applied successfully in many software vendors’ development departments. In this position paper, we address the broader agile service development. Based on method engineering principles we

  10. Sensor-based activity recognition using extended belief rule-based inference methodology.

    Science.gov (United States)

    Calzada, A; Liu, J; Nugent, C D; Wang, H; Martinez, L

    2014-01-01

    The recently developed extended belief rule-based inference methodology (RIMER+) recognizes the need of modeling different types of information and uncertainty that usually coexist in real environments. A home setting with sensors located in different rooms and on different appliances can be considered as a particularly relevant example of such an environment, which brings a range of challenges for sensor-based activity recognition. Although RIMER+ has been designed as a generic decision model that could be applied in a wide range of situations, this paper discusses how this methodology can be adapted to recognize human activities using binary sensors within smart environments. The evaluation of RIMER+ against other state-of-the-art classifiers in terms of accuracy, efficiency and applicability was found to be significantly relevant, specially in situations of input data incompleteness, and it demonstrates the potential of this methodology and underpins the basis to develop further research on the topic.

  11. An Enhanced Rule-Based Web Scanner Based on Similarity Score

    Directory of Open Access Journals (Sweden)

    LEE, M.

    2016-08-01

    Full Text Available This paper proposes an enhanced rule-based web scanner in order to get better accuracy in detecting web vulnerabilities than the existing tools, which have relatively high false alarm rate when the web pages are installed in unconventional directory paths. Using the proposed matching method based on similarity score, the proposed scheme can determine whether two pages have the same vulnerabilities or not. With this method, the proposed scheme is able to figure out the target web pages are vulnerable by comparing them to the web pages that are known to have vulnerabilities. We show the proposed scanner reduces 12% false alarm rate compared to the existing well-known scanner through the performance evaluation via various experiments. The proposed scheme is especially helpful in detecting vulnerabilities of the web applications which come from well-known open-source web applications after small customization, which happens frequently in many small-sized companies.

  12. Ruled-based control of off-grid desalination powered by renewable energies

    Directory of Open Access Journals (Sweden)

    Alvaro Serna

    2015-08-01

    Full Text Available A rule-based control is presented for desalination plants operating under variable, renewable power availability. This control algorithm is based on two sets of rules: first, a list that prioritizes the reverse osmosis (RO units of the plant is created, based on the current state and the expected water demand; secondly, the available energy is then dispatched to these units following this prioritized list. The selected strategy is tested on a specific case study: a reverse osmosis plant designed for the production of desalinated water powered by wind and wave energy. Simulation results illustrate the correct performance of the plant under this control.

  13. Rules Extraction with an Immune Algorithm

    Directory of Open Access Journals (Sweden)

    Deqin Yan

    2007-12-01

    Full Text Available In this paper, a method of extracting rules with immune algorithms from information systems is proposed. Designing an immune algorithm is based on a sharing mechanism to extract rules. The principle of sharing and competing resources in the sharing mechanism is consistent with the relationship of sharing and rivalry among rules. In order to extract rules efficiently, a new concept of flexible confidence and rule measurement is introduced. Experiments demonstrate that the proposed method is effective.

  14. Evaluation of wholesale electric power market rules and financial risk management by agent-based simulations

    Science.gov (United States)

    Yu, Nanpeng

    As U.S. regional electricity markets continue to refine their market structures, designs and rules of operation in various ways, two critical issues are emerging. First, although much experience has been gained and costly and valuable lessons have been learned, there is still a lack of a systematic platform for evaluation of the impact of a new market design from both engineering and economic points of view. Second, the transition from a monopoly paradigm characterized by a guaranteed rate of return to a competitive market created various unfamiliar financial risks for various market participants, especially for the Investor Owned Utilities (IOUs) and Independent Power Producers (IPPs). This dissertation uses agent-based simulation methods to tackle the market rules evaluation and financial risk management problems. The California energy crisis in 2000-01 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This dissertation presents a flexible and integrative method to assess market designs through agent-based simulations. Realistic simulation scenarios on a 225-bus system are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GenCo) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. The importance of financial risk management is exemplified by the recent financial crisis. In this

  15. Graphical matching rules for cardinality based service feature diagrams

    Directory of Open Access Journals (Sweden)

    Faiza Kanwal

    2017-03-01

    Full Text Available To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.

  16. Optimal operating rules definition in complex water resource systems combining fuzzy logic, expert criteria and stochastic programming

    Science.gov (United States)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2016-04-01

    This contribution presents a methodology for defining optimal seasonal operating rules in multireservoir systems coupling expert criteria and stochastic optimization. Both sources of information are combined using fuzzy logic. The structure of the operating rules is defined based on expert criteria, via a joint expert-technician framework consisting in a series of meetings, workshops and surveys carried out between reservoir managers and modelers. As a result, the decision-making process used by managers can be assessed and expressed using fuzzy logic: fuzzy rule-based systems are employed to represent the operating rules and fuzzy regression procedures are used for forecasting future inflows. Once done that, a stochastic optimization algorithm can be used to define optimal decisions and transform them into fuzzy rules. Finally, the optimal fuzzy rules and the inflow prediction scheme are combined into a Decision Support System for making seasonal forecasts and simulate the effect of different alternatives in response to the initial system state and the foreseen inflows. The approach presented has been applied to the Jucar River Basin (Spain). Reservoir managers explained how the system is operated, taking into account the reservoirs' states at the beginning of the irrigation season and the inflows previewed during that season. According to the information given by them, the Jucar River Basin operating policies were expressed via two fuzzy rule-based (FRB) systems that estimate the amount of water to be allocated to the users and how the reservoir storages should be balanced to guarantee those deliveries. A stochastic optimization model using Stochastic Dual Dynamic Programming (SDDP) was developed to define optimal decisions, which are transformed into optimal operating rules embedding them into the two FRBs previously created. As a benchmark, historical records are used to develop alternative operating rules. A fuzzy linear regression procedure was employed to

  17. A rule-based reference resolution method for Dutch discourse

    NARCIS (Netherlands)

    Harabagiu, S.; op den Akker, Hendrikus J.A.; Hospers, M.A.; Ferrandez, A.; Kroezen, Erna; Nijholt, Antinus; Lie, Danny

    2002-01-01

    This paper presents a knowledge-poor method for the solution of anaphoric and deictic expressions in Dutch texts. The method is developed for use in a text summarization system. Anaphora resolution plays an important role in the analysis of the original text as well as in the generation of the text

  18. Optimal offering and operating strategies for wind-storage systems with linear decision rules

    DEFF Research Database (Denmark)

    Ding, Huajie; Pinson, Pierre; Hu, Zechun

    2016-01-01

    The participation of wind farm-energy storage systems (WF-ESS) in electricity markets calls for an integrated view of day-ahead offering strategies and real-time operation policies. Such an integrated strategy is proposed here by co-optimizing offering at the day-ahead stage and operation policy...... to be used at the balancing stage. Linear decision rules are seen as a natural approach to model and optimize the real-time operation policy. These allow enhancing profits from balancing markets based on updated information on prices and wind power generation. Our integrated strategies for WF...

  19. European Marketing Authorizations Granted Based on a Single Pivotal Clinical Trial: The Rule or the Exception?

    Science.gov (United States)

    Morant, Anne Vinther; Vestergaard, Henrik Tang

    2018-07-01

    A minimum of two positive, adequate, and well-controlled clinical trials has historically been the gold standard for providing substantial evidence to support regulatory approval of a new medicine. Nevertheless, the present analysis of European Marketing Authorizations granted between 2012 and 2016 showed that 45% of new active substances were approved based on a single pivotal clinical trial. For therapeutic areas such as oncology and cardiovascular diseases, approvals based on a single pivotal trial are the rule rather than the exception, whereas new medicines within the nervous system area were generally supported by two or more pivotal trials. While overall similar trends have been observed in the US, the recent US Food and Drug Administration approvals of nervous system medicines based on a single pivotal trial suggest that a case-by-case scientific evaluation of the totality of evidence is increasingly applied to facilitate faster access of new medicines to patients suffering from serious diseases. © 2017 American Society for Clinical Pharmacology and Therapeutics.

  20. Mutation rules and the evolution of sparseness and modularity in biological systems.

    Directory of Open Access Journals (Sweden)

    Tamar Friedlander

    Full Text Available Biological systems exhibit two structural features on many levels of organization: sparseness, in which only a small fraction of possible interactions between components actually occur; and modularity--the near decomposability of the system into modules with distinct functionality. Recent work suggests that modularity can evolve in a variety of circumstances, including goals that vary in time such that they share the same subgoals (modularly varying goals, or when connections are costly. Here, we studied the origin of modularity and sparseness focusing on the nature of the mutation process, rather than on connection cost or variations in the goal. We use simulations of evolution with different mutation rules. We found that commonly used sum-rule mutations, in which interactions are mutated by adding random numbers, do not lead to modularity or sparseness except for in special situations. In contrast, product-rule mutations in which interactions are mutated by multiplying by random numbers--a better model for the effects of biological mutations--led to sparseness naturally. When the goals of evolution are modular, in the sense that specific groups of inputs affect specific groups of outputs, product-rule mutations also lead to modular structure; sum-rule mutations do not. Product-rule mutations generate sparseness and modularity because they tend to reduce interactions, and to keep small interaction terms small.

  1. Mode Selection Rules for a Two-Delay System with Positive and Negative Feedback Loops

    Science.gov (United States)

    Takahashi, Kin'ya; Kobayashi, Taizo

    2018-04-01

    The mode selection rules for a two-delay system, which has negative feedback with a short delay time t1 and positive feedback with a long delay time t2, are studied numerically and theoretically. We find two types of mode selection rules depending on the strength of the negative feedback. When the strength of the negative feedback |α1| (α1 0), 2m + 1-th harmonic oscillation is well sustained in a neighborhood of t1/t2 = even/odd, i.e., relevant condition. In a neighborhood of the irrelevant condition given by t1/t2 = odd/even or t1/t2 = odd/odd, higher harmonic oscillations are observed. However, if |α1| is slightly less than α2, a different mode selection rule works, where the condition t1/t2 = odd/even is relevant and the conditions t1/t2 = odd/odd and t1/t2 = even/odd are irrelevant. These mode selection rules are different from the mode selection rule of the normal two-delay system with two positive feedback loops, where t1/t2 = odd/odd is relevant and the others are irrelevant. The two types of mode selection rules are induced by individually different mechanisms controlling the Hopf bifurcation, i.e., the Hopf bifurcation controlled by the "boosted bifurcation process" and by the "anomalous bifurcation process", which occur for |α1| below and above the threshold value αth, respectively.

  2. Rule-based modularization in model transformation languages illustrated with ATL

    NARCIS (Netherlands)

    Ivanov, Ivan; van den Berg, Klaas; Jouault, Frédéric

    2007-01-01

    This paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. Two scenarios are shown in which the modular units are identified on the basis of relations between source and target metamodels and on the base of generic transformation

  3. A comparison between model and rule based control of a periodic activated sludge process

    DEFF Research Database (Denmark)

    Isaacs, Steven Howard; Thornberg, D.

    1997-01-01

    Two strategies for control of nitrogen removal in an alternating activated sludge plant are compared. One is based on simple model predictions determining the cycle length at the beginning of each cycle. The other is based on simple rules relating present ammonia and nitrate concentrations. Both ...

  4. DEVELOP-FPS: a First Person Shooter Development Tool for Rule-based Scripts

    Directory of Open Access Journals (Sweden)

    Bruno Correia

    2012-09-01

    Full Text Available We present DEVELOP-FPS, a software tool specially designed for the development of First Person Shooter (FPS players controlled by Rule Based Scripts. DEVELOP-FPS may be used by FPS developers to create, debug, maintain and compare rule base player behaviours, providing a set of useful functionalities: i for an easy preparation of the right scenarios for game debugging and testing; ii for controlling the game execution: users can stop and resume the game execution at any instant, monitoring and controlling every player in the game, monitoring the state of each player, their rule base activation, being able to issue commands to control their behaviour; and iii to automatically run a certain number of game executions and collect data in order to evaluate and compare the players performance along a sufficient number of similar experiments.

  5. Criterion learning in rule-based categorization: simulation of neural mechanism and new data.

    Science.gov (United States)

    Helie, Sebastien; Ell, Shawn W; Filoteo, J Vincent; Maddox, W Todd

    2015-04-01

    In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g., categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define 'long' and 'short'). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL's implications for future research on rule learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Automated rule-base control for nuclear power plants

    International Nuclear Information System (INIS)

    Colley, R.W.

    1983-09-01

    An effort is underway to optimize the roles of man and machine in the control of liquid-metal-cooled fast breeder reactors. The work reported here describes: (1) a methodology for the decomposition of a process into a hierarchical structure; (2) an explicit methodology, Sequencing Established States, to limit the state space search for process control; and (3) the Procedure Prompting System which demonstrates the use of the above methodologies for automatically generating instructions to provide guidance to an operator for both normal and off-normal plant conditions

  7. The GR-value deviation from the additivity rule for irradiated systems containing heterocyclic compounds

    International Nuclear Information System (INIS)

    Nanobashvili, H.M.; Shanidze, G.V.; Khidesheli, G.I.; Panchvidze, M.V.

    1988-01-01

    The investigation of the low temperature radiolysis of binary systems containing heterocyclic compounds has been carried out. In the systems under study the G R -value deviation from the additivity rule is observed due to the energy transfer processes from matrix molecules. It is shown that heterocyclic compounds are good radioprotectors. (author)

  8. A rule-based fault detection method for air handling units

    Energy Technology Data Exchange (ETDEWEB)

    Schein, J.; Bushby, S. T.; Castro, N. S. [National Institute of Standards and Technology, Gaithersburg, MD (United States); House, J. M. [Iowa Energy Center, Ankeny, IA (United States)

    2006-07-01

    Air handling unit performance assessment rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units (AHUs). Control signals are used to determine the mode of operation of the AHU. A subset of the expert rules which correspond to that mode of operation are then evaluated to determine whether a fault exists. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon the sensor data and control signals that are commonly available in these systems. APAR was tested using data sets collected from a 'hardware-in-the-loop' emulator and from several field sites. APAR was also embedded in commercial AHU controllers and tested in the emulator. (author)

  9. Apriori-based network intrusion detection system

    International Nuclear Information System (INIS)

    Wang Wenjin; Liu Junrong; Liu Baoxu

    2012-01-01

    With the development of network communication technology, more and more social activities run by Internet. In the meantime, the network information security is getting increasingly serious. Intrusion Detection System (IDS) has greatly improved the general security level of whole network. But there are still many problem exists in current IDS, e.g. high leak rate detection/false alarm rates and feature library need frequently upgrade. This paper presents an association-rule based IDS. This system can detect unknown attack by generate rules from training data. Experiment in last chapter proved the system has great accuracy on unknown attack detection. (authors)

  10. Schedule for Rating Disabilities; the Endocrine System. Final rule.

    Science.gov (United States)

    2017-11-02

    This document amends the Department of Veterans Affairs (VA) Schedule for Rating Disabilities (VASRD) by revising the portion of the Schedule that addresses endocrine conditions and disorders of the endocrine system. The effect of this action is to ensure that the VASRD uses current medical terminology and to provide detailed and updated criteria for evaluation of endocrine disorders.

  11. System size expansion using Feynman rules and diagrams

    NARCIS (Netherlands)

    Thomas, P.; Fleck, C.; Grima, R.; Popovic, N.

    2014-01-01

    Few analytical methods exist for quantitative studies of large fluctuations in stochastic systems. In this article, we develop a simple diagrammatic approach to the chemical master equation that allows us to calculate multi-time correlation functions which are accurate to any desired order in van

  12. Feedback control of nonlinear quantum systems: a rule of thumb.

    Science.gov (United States)

    Jacobs, Kurt; Lund, Austin P

    2007-07-13

    We show that in the regime in which feedback control is most effective - when measurements are relatively efficient, and feedback is relatively strong - then, in the absence of any sharp inhomogeneity in the noise, it is always best to measure in a basis that does not commute with the system density matrix than one that does. That is, it is optimal to make measurements that disturb the state one is attempting to stabilize.

  13. Inheritance rules for Hierarchical Metadata Based on ISO 19115

    Science.gov (United States)

    Zabala, A.; Masó, J.; Pons, X.

    2012-04-01

    registry is complete for each metadata hierarchical level, but at the implementation level most of the metadata elements are not stored at both levels but only at more generic one. This communication defines a metadata system that covers 4 levels, describes which metadata has to support series-layer inheritance and in which way, and how hierarchical levels are defined and stored. Metadata elements are classified according to the type of inheritance between products, series, tiles and the datasets. It explains the metadata elements classification and exemplifies it using core metadata elements. The communication also presents a metadata viewer and edition tool that uses the described model to propagate metadata elements and to show to the user a complete set of metadata for each level in a transparent way. This tool is integrated in the MiraMon GIS software.

  14. Behavior-based rules for fitness-for-duty assessment of nuclear power plant personnel

    International Nuclear Information System (INIS)

    Kennedy, R.S.

    1989-01-01

    The safe and reliable operation of nuclear power plants requires that plant personnel not be under the influence of any substance, legal or illegal, or mentally or physically impaired from any cause that in any way adversely affects their ability to safely and competently perform their duties. This goal has been formalized by the US Nuclear Regulatory Commission in their proposed rule for a fitness-for-duty program. The purpose of this paper is to describe a performance-based tool based on surrogate tests and dose equivalency methodologies that is a viable candidate for fitness-for-duty assessment. The automated performance test system (APTS) is a microcomputer-based human performance test battery that has been developed over a decade of research supported variously by the National Science Foundation, National Aeronautics and Space Administration, US Department of Energy, and the US Navy and Army. Representing the most psychometrically sound test from evaluations of over 150 well-known tests of basic psychomotor and cognitive skills, the battery provides direct prediction of a worker's fitness for duty. Twenty-four tests are suitable for use, and a dozen have thus far been shown to be sensitive to the effects of legal and illegal drugs, alcohol, fatigue, stress, and other causes of impairment

  15. iRODS Primer Integrated Rule-Oriented Data System

    CERN Document Server

    Rajasekar, Arcot

    2010-01-01

    Policy-based data management enables the creation of community-specific collections. Every collection is created for a purpose. The purpose defines the set of properties that will be associated with the collection. The properties are enforced by management policies that control the execution of procedures that are applied whenever data are ingested or accessed. The procedures generate state information that defines the outcome of enforcing the management policy. The state information can be queried to validate assessment criteria and verify that the required collection properties have been con

  16. Quality assurance in central nuclear power plant control systems. (Status report containing proposed enhancements for KTA rules)

    International Nuclear Information System (INIS)

    Gossner, S.

    1985-01-01

    All enterprises investigated observe the requirements laid down in KTA 1401. In most cases, the quality assurance systems and measures applied even go beyond the requirements of KTA 1401, especially in those enterprises working primarily for export and having to meet foreign quality assurance standards. Quality assurance measures in these enterprises are based primarily on 10 CFR 50, App.B and related rules and standards (e.g. ANSI N 54.2; NUREG 75/087). Internal quality assurance in these enterprises is organized on the basis of graphic flow diagrams which are even presented in the quality assurance manuals. These flow diagrams, in contrast to the German KTA rules, meet the international standards for quality assurance. KTA 1401 requirements not sufficiently met are, e.g. the operator audits with plant producers and unit and equipment producer audits with component producers. The report presents hints for improvements of the quality assurance concept in control systems engineering. (orig./HP) [de

  17. Re-Evaluation of Acid-Base Prediction Rules in Patients with Chronic Respiratory Acidosis

    Directory of Open Access Journals (Sweden)

    Tereza Martinu

    2003-01-01

    Full Text Available RATIONALE: The prediction rules for the evaluation of the acid-base status in patients with chronic respiratory acidosis, derived primarily from an experimental canine model, suggest that complete compensation should not occur. This appears to contradict frequent observations of normal or near-normal pH levels in patients with chronic hypercapnia.

  18. Control of Angra 1' PZR by a fuzzy rule base build through genetic programming

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2002-01-01

    There is an optimum pressure for the normal operation of nuclear power plant reactors and thresholds that must be respected during transients, what make the pressurizer an important control mechanism. Inside a pressurizer there are heaters and a shower. From their actuation levels, they control the vapor pressure inside the pressurizer and, consequently, inside the primary circuit. Therefore, the control of the pressurizer consists in controlling the actuation levels of the heaters and of the shower. In the present work this function is implemented through a fuzzy controller. Besides the efficient way of exerting control, this approach presents the possibility of extracting knowledge of how this control is been made. A fuzzy controller consists basically in an inference machine and a rule base, the later been constructed with specialized knowledge. In some circumstances, however, this knowledge is not accurate, and may lead to non-efficient results. With the development of artificial intelligence techniques, there wore found methods to substitute specialists, simulating its knowledge. Genetic programming is an evolutionary algorithm particularly efficient in manipulating rule base structures. In this work genetic programming was used as a substitute for the specialist. The goal is to test if an irrational object, a computer, is capable, by it self, to find out a rule base reproducing a pre-established actuation levels profile. The result is positive, with the discovery of a fuzzy rule base presenting an insignificant error. A remarkable result that proves the efficiency of the approach. (author)

  19. Rule-based emotion detection on social media : putting tweets on Plutchik's wheel

    NARCIS (Netherlands)

    Tromp, E.; Pechenizkiy, M.

    2014-01-01

    We study sentiment analysis beyond the typical granularity of polarity and instead use Plutchik's wheel of emotions model. We introduce RBEM-Emo as an extension to the Rule-Based Emission Model algorithm to deduce such emotions from human-written messages. We evaluate our approach on two different

  20. Rule-based versus probabilistic selection for active surveillance using three definitions of insignificant prostate cancer

    NARCIS (Netherlands)

    L.D.F. Venderbos (Lionne); M.J. Roobol-Bouts (Monique); C.H. Bangma (Chris); R.C.N. van den Bergh (Roderick); L.P. Bokhorst (Leonard); D. Nieboer (Daan); Godtman, R; J. Hugosson (Jonas); van der Kwast, T; E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractTo study whether probabilistic selection by the use of a nomogram could improve patient selection for active surveillance (AS) compared to the various sets of rule-based AS inclusion criteria currently used. We studied Dutch and Swedish patients participating in the European Randomized

  1. A rule-based backchannel prediction model using pitch and pause information

    NARCIS (Netherlands)

    Truong, Khiet Phuong; Poppe, Ronald Walter; Heylen, Dirk K.J.

    We manually designed rules for a backchannel (BC) prediction model based on pitch and pause information. In short, the model predicts a BC when there is a pause of a certain length that is preceded by a falling or rising pitch. This model was validated against the Dutch IFADV Corpus in a

  2. Derivation of optimal joint operating rules for multi-purpose multi-reservoir water-supply system

    Science.gov (United States)

    Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wang, Chao; Lei, Xiao-hui; Xiong, Yi-song; Zhang, Wei

    2017-08-01

    The derivation of joint operating policy is a challenging task for a multi-purpose multi-reservoir system. This study proposed an aggregation-decomposition model to guide the joint operation of multi-purpose multi-reservoir system, including: (1) an aggregated model based on the improved hedging rule to ensure the long-term water-supply operating benefit; (2) a decomposed model to allocate the limited release to individual reservoirs for the purpose of maximizing the total profit of the facing period; and (3) a double-layer simulation-based optimization model to obtain the optimal time-varying hedging rules using the non-dominated sorting genetic algorithm II, whose objectives were to minimize maximum water deficit and maximize water supply reliability. The water-supply system of Li River in Guangxi Province, China, was selected for the case study. The results show that the operating policy proposed in this study is better than conventional operating rules and aggregated standard operating policy for both water supply and hydropower generation due to the use of hedging mechanism and effective coordination among multiple objectives.

  3. Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Bima Sena Bayu Dewantara

    2014-12-01

    Full Text Available Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trial‐error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time. Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorithm

  4. Multilevel Association Rule Mining for Bridge Resource Management Based on Immune Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Ou

    2014-01-01

    Full Text Available This paper is concerned with the problem of multilevel association rule mining for bridge resource management (BRM which is announced by IMO in 2010. The goal of this paper is to mine the association rules among the items of BRM and the vessel accidents. However, due to the indirect data that can be collected, which seems useless for the analysis of the relationship between items of BIM and the accidents, the cross level association rules need to be studied, which builds the relation between the indirect data and items of BRM. In this paper, firstly, a cross level coding scheme for mining the multilevel association rules is proposed. Secondly, we execute the immune genetic algorithm with the coding scheme for analyzing BRM. Thirdly, based on the basic maritime investigation reports, some important association rules of the items of BRM are mined and studied. Finally, according to the results of the analysis, we provide the suggestions for the work of seafarer training, assessment, and management.

  5. Numerical Solution of Nonlinear Volterra Integral Equations System Using Simpson’s 3/8 Rule

    Directory of Open Access Journals (Sweden)

    Adem Kılıçman

    2012-01-01

    Full Text Available The Simpson’s 3/8 rule is used to solve the nonlinear Volterra integral equations system. Using this rule the system is converted to a nonlinear block system and then by solving this nonlinear system we find approximate solution of nonlinear Volterra integral equations system. One of the advantages of the proposed method is its simplicity in application. Further, we investigate the convergence of the proposed method and it is shown that its convergence is of order O(h4. Numerical examples are given to show abilities of the proposed method for solving linear as well as nonlinear systems. Our results show that the proposed method is simple and effective.

  6. Long-Term Homeostatic Properties Complementary to Hebbian Rules in CuPc-Based Multifunctional Memristor

    Science.gov (United States)

    Wang, Laiyuan; Wang, Zhiyong; Lin, Jinyi; Yang, Jie; Xie, Linghai; Yi, Mingdong; Li, Wen; Ling, Haifeng; Ou, Changjin; Huang, Wei

    2016-10-01

    Most simulations of neuroplasticity in memristors, which are potentially used to develop artificial synapses, are confined to the basic biological Hebbian rules. However, the simplex rules potentially can induce excessive excitation/inhibition, even collapse of neural activities, because they neglect the properties of long-term homeostasis involved in the frameworks of realistic neural networks. Here, we develop organic CuPc-based memristors of which excitatory and inhibitory conductivities can implement both Hebbian rules and homeostatic plasticity, complementary to Hebbian patterns and conductive to the long-term homeostasis. In another adaptive situation for homeostasis, in thicker samples, the overall excitement under periodic moderate stimuli tends to decrease and be recovered under intense inputs. Interestingly, the prototypes can be equipped with bio-inspired habituation and sensitization functions outperforming the conventional simplified algorithms. They mutually regulate each other to obtain the homeostasis. Therefore, we develop a novel versatile memristor with advanced synaptic homeostasis for comprehensive neural functions.

  7. Simple rules can guide whether land- or ocean-based conservation will best benefit marine ecosystems.

    Science.gov (United States)

    Saunders, Megan I; Bode, Michael; Atkinson, Scott; Klein, Carissa J; Metaxas, Anna; Beher, Jutta; Beger, Maria; Mills, Morena; Giakoumi, Sylvaine; Tulloch, Vivitskaia; Possingham, Hugh P

    2017-09-01

    Coastal marine ecosystems can be managed by actions undertaken both on the land and in the ocean. Quantifying and comparing the costs and benefits of actions in both realms is therefore necessary for efficient management. Here, we quantify the link between terrestrial sediment runoff and a downstream coastal marine ecosystem and contrast the cost-effectiveness of marine- and land-based conservation actions. We use a dynamic land- and sea-scape model to determine whether limited funds should be directed to 1 of 4 alternative conservation actions-protection on land, protection in the ocean, restoration on land, or restoration in the ocean-to maximise the extent of light-dependent marine benthic habitats across decadal timescales. We apply the model to a case study for a seagrass meadow in Australia. We find that marine restoration is the most cost-effective action over decadal timescales in this system, based on a conservative estimate of the rate at which seagrass can expand into a new habitat. The optimal decision will vary in different social-ecological contexts, but some basic information can guide optimal investments to counteract land- and ocean-based stressors: (1) marine restoration should be prioritised if the rates of marine ecosystem decline and expansion are similar and low; (2) marine protection should take precedence if the rate of marine ecosystem decline is high or if the adjacent catchment is relatively intact and has a low rate of vegetation decline; (3) land-based actions are optimal when the ratio of marine ecosystem expansion to decline is greater than 1:1.4, with terrestrial restoration typically the most cost-effective action; and (4) land protection should be prioritised if the catchment is relatively intact but the rate of vegetation decline is high. These rules of thumb illustrate how cost-effective conservation outcomes for connected land-ocean systems can proceed without complex modelling.

  8. Application of rule-based data mining techniques to real time ATLAS Grid job monitoring data

    CERN Document Server

    Ahrens, R; The ATLAS collaboration; Kalinin, S; Maettig, P; Sandhoff, M; dos Santos, T; Volkmer, F

    2012-01-01

    The Job Execution Monitor (JEM) is a job-centric grid job monitoring software developed at the University of Wuppertal and integrated into the pilot-based “PanDA” job brokerage system leveraging physics analysis and Monte Carlo event production for the ATLAS experiment on the Worldwide LHC Computing Grid (WLCG). With JEM, job progress and grid worker node health can be supervised in real time by users, site admins and shift personnel. Imminent error conditions can be detected early and countermeasures can be initiated by the Job’s owner immideatly. Grid site admins can access aggregated data of all monitored jobs to infer the site status and to detect job and Grid worker node misbehaviour. Shifters can use the same aggregated data to quickly react to site error conditions and broken production tasks. In this work, the application of novel data-centric rule based methods and data-mining techniques to the real time monitoring data is discussed. The usage of such automatic inference techniques on monitorin...

  9. 76 FR 75911 - Certain Video Game Systems and Controllers; Investigations: Terminations, Modifications and Rulings

    Science.gov (United States)

    2011-12-05

    ... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-743] Certain Video Game Systems and Controllers; Investigations: Terminations, Modifications and Rulings AGENCY: U.S. International Trade Commission. ACTION: Notice. Section 337 of the Tariff Act of 1930 provides that if the Commission finds a violation it shall exclude the articles...

  10. 75 FR 60632 - Hazardous Waste Management System; Identification and Listing of Hazardous Waste; Direct Final Rule

    Science.gov (United States)

    2010-10-01

    ... Waste Management System; Identification and Listing of Hazardous Waste; Direct Final Rule AGENCY... management and treatment of several F- and K-waste codes. These waste codes are F037, F038, K048, K049, K051... released from the waste, plausible and specific types of management of the petitioned waste, the quantities...

  11. 75 FR 60689 - Hazardous Waste Management System; Identification and Listing of Hazardous Waste; Proposed Rule

    Science.gov (United States)

    2010-10-01

    ... Waste Management System; Identification and Listing of Hazardous Waste; Proposed Rule AGENCY... exclude (or delist) a certain solid waste generated by its Beaumont, Texas, facility from the lists of hazardous wastes. EPA used the Delisting Risk Assessment Software (DRAS) Version 3.0 in the evaluation of...

  12. Rules of Normalisation and their Importance for Interpretation of Systems of Optimal Taxation

    DEFF Research Database (Denmark)

    Munk, Knud Jørgen

    representation of the general equilibrium conditions the rules of normalisation in standard optimal tax models. This allows us to provide an intuitive explanation of what determines the optimal tax system. Finally, we review a number of examples where lack of precision with respect to normalisation in otherwise...... important contributions to the literature on optimal taxation has given rise to misinterpretations of of analytical results....

  13. 76 FR 5110 - Hazardous Waste Management System; Identification and Listing of Hazardous Waste; Proposed Rule

    Science.gov (United States)

    2011-01-28

    ... will dispose of the leachate at a publicly owned treatment works or at an industrial waste disposal... classification of listed waste pursuant to Sec. Sec. 261.31 and 261.32. Specifically, in its petition, Gulf West... Waste Management System; Identification and Listing of Hazardous Waste; Proposed Rule AGENCY...

  14. Assessing Performance of Multipurpose Reservoir System Using Two-Point Linear Hedging Rule

    Science.gov (United States)

    Sasireka, K.; Neelakantan, T. R.

    2017-07-01

    Reservoir operation is the one of the important filed of water resource management. Innovative techniques in water resource management are focussed at optimizing the available water and in decreasing the environmental impact of water utilization on the natural environment. In the operation of multi reservoir system, efficient regulation of the release to satisfy the demand for various purpose like domestic, irrigation and hydropower can lead to increase the benefit from the reservoir as well as significantly reduces the damage due to floods. Hedging rule is one of the emerging techniques in reservoir operation, which reduce the severity of drought by accepting number of smaller shortages. The key objective of this paper is to maximize the minimum power production and improve the reliability of water supply for municipal and irrigation purpose by using hedging rule. In this paper, Type II two-point linear hedging rule is attempted to improve the operation of Bargi reservoir in the Narmada basin in India. The results obtained from simulation of hedging rule is compared with results from Standard Operating Policy, the result shows that the application of hedging rule significantly improved the reliability of water supply and reliability of irrigation release and firm power production.

  15. A rule of seven in Watson-Crick base-pairing of mismatched sequences.

    Science.gov (United States)

    Cisse, Ibrahim I; Kim, Hajin; Ha, Taekjip

    2012-05-13

    Sequence recognition through base-pairing is essential for DNA repair and gene regulation, but the basic rules governing this process remain elusive. In particular, the kinetics of annealing between two imperfectly matched strands is not well characterized, despite its potential importance in nucleic acid-based biotechnologies and gene silencing. Here we use single-molecule fluorescence to visualize the multiple annealing and melting reactions of two untethered strands inside a porous vesicle, allowing us to precisely quantify the annealing and melting rates. The data as a function of mismatch position suggest that seven contiguous base pairs are needed for rapid annealing of DNA and RNA. This phenomenological rule of seven may underlie the requirement for seven nucleotides of complementarity to seed gene silencing by small noncoding RNA and may help guide performance improvement in DNA- and RNA-based bio- and nanotechnologies, in which off-target effects can be detrimental.

  16. Achieving superior band gap, refractive index and morphology in composite oxide thin film systems violating the Moss rule

    International Nuclear Information System (INIS)

    Sahoo, N K; Thakur, S; Tokas, R B

    2006-01-01

    The interrelation between energy gap and high frequency refractive index in semiconductors and dielectrics is manifested by an inverse law which is popularly known as the Moss rule. This semi-empirical relationship is based on the fundamental principle that in a dielectric medium all energy levels are scaled down by a factor of the square of the dielectric constant. Such a rule is obeyed by most pure semiconductors and dielectrics with a few rare violations in composite materials which display several interesting parametric and microstructural evolutions. The present results are based on some specific oxide composite thin films involving Gd 2 O 3 /SiO 2 and ZrO 2 /SiO 2 codeposited systems that have displayed a superior refractive index and energy gaps violating the semi-empirical Moss rule. Also, morphological supremacy is also distinctly noticed in these composites. The novel microstructural and polarizability properties of such composite systems were probed through multi-mode atomic force microscopy and phase modulated spectroscopic ellipsometry using refractive index modelling, autocorrelation and height-height correlation functional analyses. These binary composite thin films have shown their potential as well as the possibility of meeting expectations in satisfying the challenging optical coating requirements of the deep ultraviolet spectral region

  17. Selection rules for single-chain-magnet behaviour in non-collinear Ising systems

    Energy Technology Data Exchange (ETDEWEB)

    Vindigni, Alessandro [Laboratorium fuer Festkoerperphysik, ETH Zuerich, CH-8093 Zuerich (Switzerland); Pini, Maria Gloria [Istituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (Italy)], E-mail: vindigni@phys.ethz.ch

    2009-06-10

    The magnetic behaviour of molecular single-chain magnets is investigated in the framework of a one-dimensional Ising model with single spin-flip Glauber dynamics. Opportune modifications to the original theory are required in order to account for non-collinearity of local anisotropy axes between themselves and with respect to the crystallographic (laboratory) frame. The extension of Glauber's theory to the case of a collinear Ising ferrimagnetic chain is also discussed. Within this formalism, both the dynamics of magnetization reversal in zero field and the response of the system to a weak magnetic field, oscillating in time, are studied. Depending on the experimental geometry, selection rules are found for the occurrence of slow relaxation of the magnetization at low temperatures, as well as for resonant behaviour of the a.c. susceptibility as a function of temperature at low frequencies. The present theory applies successfully to some real systems, namely Mn-, Dy- and Co-based molecular magnetic chains, showing that single-chain-magnet behaviour is not only a feature of collinear ferro- and ferrimagnetic, but also of canted antiferromagnetic chains.

  18. Selection rules for single-chain-magnet behaviour in non-collinear Ising systems

    International Nuclear Information System (INIS)

    Vindigni, Alessandro; Pini, Maria Gloria

    2009-01-01

    The magnetic behaviour of molecular single-chain magnets is investigated in the framework of a one-dimensional Ising model with single spin-flip Glauber dynamics. Opportune modifications to the original theory are required in order to account for non-collinearity of local anisotropy axes between themselves and with respect to the crystallographic (laboratory) frame. The extension of Glauber's theory to the case of a collinear Ising ferrimagnetic chain is also discussed. Within this formalism, both the dynamics of magnetization reversal in zero field and the response of the system to a weak magnetic field, oscillating in time, are studied. Depending on the experimental geometry, selection rules are found for the occurrence of slow relaxation of the magnetization at low temperatures, as well as for resonant behaviour of the a.c. susceptibility as a function of temperature at low frequencies. The present theory applies successfully to some real systems, namely Mn-, Dy- and Co-based molecular magnetic chains, showing that single-chain-magnet behaviour is not only a feature of collinear ferro- and ferrimagnetic, but also of canted antiferromagnetic chains.

  19. Getting Objects Methods and Interactions by Extracting Business Rules from Legacy Systems

    Directory of Open Access Journals (Sweden)

    Omar El Beggar

    2014-08-01

    Full Text Available The maintenance of legacy systems becomes over the years extremely complex and highly expensive due to the incessant changes of company activities and policies. In this case, a new or an improved system must replace the previous one. However, replacing those systems completely from scratch is also very expensive and it represents a huge risk. The optimal scenario is evolving those systems by profiting from the valuable knowledge embedded in them. This paper aims to present an approach for knowledge acquisition from existing legacy systems by extracting business rules from source code. In fact, the business rules are extracted and assigned next to the domain entities in order to generate objects methods and interactions in an object-oriented platform. Furthermore, a rules translation in natural language is given. The aim is advancing a solution for re-engineering legacy systems, minimize the cost of their modernization and keep very small the gap between the company business and the renovated systems.

  20. SPATKIN: a simulator for rule-based modeling of biomolecular site dynamics on surfaces.

    Science.gov (United States)

    Kochanczyk, Marek; Hlavacek, William S; Lipniacki, Tomasz

    2017-11-15

    Rule-based modeling is a powerful approach for studying biomolecular site dynamics. Here, we present SPATKIN, a general-purpose simulator for rule-based modeling in two spatial dimensions. The simulation algorithm is a lattice-based method that tracks Brownian motion of individual molecules and the stochastic firing of rule-defined reaction events. Because rules are used as event generators, the algorithm is network-free, meaning that it does not require to generate the complete reaction network implied by rules prior to simulation. In a simulation, each molecule (or complex of molecules) is taken to occupy a single lattice site that cannot be shared with another molecule (or complex). SPATKIN is capable of simulating a wide array of membrane-associated processes, including adsorption, desorption and crowding. Models are specified using an extension of the BioNetGen language, which allows to account for spatial features of the simulated process. The C ++ source code for SPATKIN is distributed freely under the terms of the GNU GPLv3 license. The source code can be compiled for execution on popular platforms (Windows, Mac and Linux). An installer for 64-bit Windows and a macOS app are available. The source code and precompiled binaries are available at the SPATKIN Web site (http://pmbm.ippt.pan.pl/software/spatkin). spatkin.simulator@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  1. [Analyze prescription rules of Professor Jiang Liangduo treatment for abdominal mass based on traditional Chinese medicine inheritance platform].

    Science.gov (United States)

    Lian, Xiao-Xiao; Guo, Xiao-Xia

    2018-01-01

    To investigate the herbal prescription rules of Professor Jiang Liangduo in the treatment of abdominal mass based on the traditional Chinese medicine inheritance support system software (TCMISS) of version 2.5, find out new herbal formulas for the treatment of abdominal mass, and then provide new reference to its traditional Chinese medicine therapy. By the method of retrospective study, one hundred and thirty-two outpatient prescriptions of Professor Jiang for the treatment of abdominal mass were collected to establish a typical database with TCMISS. Four properties, five tastes, channel tropism, frequency count, Chinese herbal prescriptions rules and the new prescriptions were analyzed so as to dig out the prescription rules. There were 57 herbs with a frequency>=15, and then 91 core combinations of 2-5 herbs were evolved and 9 new prescriptions were created. It was found out that these drugs mainly had the effects of liver nourishing and soothing, soft-moist and dredging-tonifying, supporting right and dispeling evil, cooperating with the method of calming the liver and resolving hard lump according to the actual situation. It reflected the thought of treatment based on syndrome differentiation in TCM, and provided a new reference for its clinical treatment and research. Copyright© by the Chinese Pharmaceutical Association.

  2. Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

    Science.gov (United States)

    Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F

    2017-03-01

    This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. 78 FR 58153 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

    Science.gov (United States)

    2013-09-23

    ... American Industry Classification System Based Federal Wage System Wage Surveys AGENCY: U.S. Office of... in Federal Wage System wage survey industry regulations with the 2012 NAICS revisions published by.... Applicability date: This rule applies for local wage surveys beginning on or after February 21, 2014. FOR...

  4. An investigation of some quantum systems using modified quantization rule form

    Energy Technology Data Exchange (ETDEWEB)

    Maiz, F., E-mail: fethimaiz@gmail.com [University of Cartage, Nabeul Engineering Preparatory Institute, Merazka, 8000 Nabeul (Tunisia); King Khalid University, Faculty of Science, Physics Department, P.O. Box 9004, Abha 61413 (Saudi Arabia)

    2014-09-15

    We propose a new simple quantization rule form: J{sub n}=nπ+δ(n), for exactly solvable and nonsolvable quantum systems. Here, J{sub n} is the momentum integral between two turning points, n the principal quantum number, and δ(n) is a function of potential parameters and n. This new quantization rule form is a generalization of the conventional one, already developed for exactly solvable quantum systems. We found that δ(n) is a constant independent of n for exactly solvable quantum systems. We carry out the expression of δ(n) for V-shape potential, and show that it takes this form δ(n)=(π/2)+(1/a+bn+cn{sup 2}) for anharmonic oscillators potential V(x)=αx{sup p}+βx{sup 2}.

  5. The semi-Markov process. Generalizations and calculation rules for application in the analysis of systems

    International Nuclear Information System (INIS)

    Hirschmann, H.

    1983-06-01

    The consequences of the basic assumptions of the semi-Markov process as defined from a homogeneous renewal process with a stationary Markov condition are reviewed. The notion of the semi-Markov process is generalized by its redefinition from a nonstationary Markov renewal process. For both the nongeneralized and the generalized case a representation of the first order conditional state probabilities is derived in terms of the transition probabilities of the Markov renewal process. Some useful calculation rules (regeneration rules) are derived for the conditional state probabilities of the semi-Markov process. Compared to the semi-Markov process in its usual definition the generalized process allows the analysis of a larger class of systems. For instance systems with arbitrarily distributed lifetimes of their components can be described. There is also a chance to describe systems which are modified during time by forces or manipulations from outside. (Auth.)

  6. Efficient ecologic and economic operational rules for dammed systems by means of nondominated sorting genetic algorithm II

    Science.gov (United States)

    Niayifar, A.; Perona, P.

    2015-12-01

    River impoundment by dams is known to strongly affect the natural flow regime and in turn the river attributes and the related ecosystem biodiversity. Making hydropower sustainable implies to seek for innovative operational policies able to generate dynamic environmental flows while maintaining economic efficiency. For dammed systems, we build the ecological and economical efficiency plot for non-proportional flow redistribution operational rules compared to minimal flow operational. As for the case of small hydropower plants (e.g., see the companion paper by Gorla et al., this session), we use a four parameters Fermi-Dirac statistical distribution to mathematically formulate non-proportional redistribution rules. These rules allocate a fraction of water to the riverine environment depending on current reservoir inflows and storage. Riverine ecological benefits associated to dynamic environmental flows are computed by integrating the Weighted Usable Area (WUA) for fishes with Richter's hydrological indicators. Then, we apply nondominated sorting genetic algorithm II (NSGA-II) to an ensemble of non-proportional and minimal flow redistribution rules in order to generate the Pareto frontier showing the system performances in the ecologic and economic space. This fast and elitist multiobjective optimization method is eventually applied to a case study. It is found that non-proportional dynamic flow releases ensure maximal power production on the one hand, while conciliating ecological sustainability on the other hand. Much of the improvement in the environmental indicator is seen to arise from a better use of the reservoir storage dynamics, which allows to capture, and laminate flood events while recovering part of them for energy production. In conclusion, adopting such new operational policies would unravel a spectrum of globally-efficient performances of the dammed system when compared with those resulting from policies based on constant minimum flow releases.

  7. Exact substitute processes for diffusion-reaction systems with local complete exclusion rules

    International Nuclear Information System (INIS)

    Schulz, Michael; Reineker, Peter

    2005-01-01

    Lattice systems with one species diffusion-reaction processes under local complete exclusion rules are studied analytically starting from the usual master equations with discrete variables and their corresponding representation in a Fock space. On this basis, a formulation of the transition probability as a Grassmann path integral is derived in a straightforward manner. It will be demonstrated that this Grassmann path integral is equivalent to a set of Ito stochastic differential equations. Averages of arbitrary variables and correlation functions of the underlying diffusion-reaction system can be expressed as weighted averages over all solutions of the system of stochastic differential equations. Furthermore, these differential equations are equivalent to a Fokker-Planck equation describing the probability distribution of the actual Ito solutions. This probability distribution depends on continuous variables in contrast to the original master equation, and their stochastic dynamics may be interpreted as a substitute process which is completely equivalent to the original lattice dynamics. Especially, averages and correlation functions of the continuous variables are connected to the corresponding lattice quantities by simple relations. Although the substitute process for diffusion-reaction systems with exclusion rules has some similarities to the well-known substitute process for the same system without exclusion rules, there exists a set of remarkable differences. The given approach is not only valid for the discussed single-species processes. We give sufficient arguments to show that arbitrary combinations of unimolecular and bimolecular lattice reactions under complete local exclusions may be described in terms of our approach

  8. Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

    Science.gov (United States)

    van Ginneken, Bram

    2017-03-01

    Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

  9. A Novel Method of Interestingness Measures for Association Rules Mining Based on Profit

    Directory of Open Access Journals (Sweden)

    Chunhua Ju

    2015-01-01

    Full Text Available Association rules mining is an important topic in the domain of data mining and knowledge discovering. Some papers have presented several interestingness measure methods; the most typical are Support, Confidence, Lift, Improve, and so forth. But their limitations are obvious, like no objective criterion, lack of statistical base, disability of defining negative relationship, and so forth. This paper proposes three new methods, Bi-lift, Bi-improve, and Bi-confidence, for Lift, Improve, and Confidence, respectively. Then, on the basis of utility function and the executing cost of rules, we propose interestingness function based on profit (IFBP considering subjective preferences and characteristics of specific application object. Finally, a novel measure framework is proposed to improve the traditional one through experimental analysis. In conclusion, the new methods and measure framework are prior to the traditional ones in the aspects of objective criterion, comprehensive definition, and practical application.

  10. From micro to macro quantum systems a unified formalism with superselection rules and its applications

    CERN Document Server

    Kong Wan, K

    2006-01-01

    Traditional quantum theory has a very rigid structure, making it difficult to accommodate new properties emerging from novel systems. This book presents a flexible and unified theory for physical systems, from micro and macro quantum to classical. This is achieved by incorporating superselection rules and maximal symmetric operators into the theory. The resulting theory is applicable to classical, microscopic quantum and non-orthodox mixed quantum systems of which macroscopic quantum systems are examples. A unified formalism also greatly facilitates the discussion of interactions between these

  11. Fuzzy Rule-based Analysis of Promotional Efficiency in Vietnam’s Tourism Industry

    OpenAIRE

    Nguyen Quang VINH; Dam Van KHANH; Nguyen Viet ANH

    2015-01-01

    This study aims to determine an effective method of measuring the efficiency of promotional strategies for tourist destinations. Complicating factors that influence promotional efficiency (PE), such as promotional activities (PA), destination attribute (DA), and destination image (DI), make it difficult to evaluate the effectiveness of PE. This study develops a rule-based decision support mechanism using fuzzy set theory and the Analytic Hierarchy Process (AHP) to evaluate the effectiveness o...

  12. Three dimensional pattern recognition using feature-based indexing and rule-based search

    Science.gov (United States)

    Lee, Jae-Kyu

    In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

  13. Design of operating rules in complex water resources systems using historical records, expert criteria and fuzzy logic

    Science.gov (United States)

    Pulido-Velazquez, Manuel; Macian-Sorribes, Hector; María Benlliure-Moreno, Jose; Fullana-Montoro, Juan

    2015-04-01

    Water resources systems in areas with a strong tradition in water use are complex to manage by the high amount of constraints that overlap in time and space, creating a complicated framework in which past, present and future collide between them. In addition, it is usual to find "hidden constraints" in system operations, which condition operation decisions being unnoticed by anyone but the river managers and users. Being aware of those hidden constraints requires usually years of experience and a degree of involvement in that system's management operations normally beyond the possibilities of technicians. However, their impact in the management decisions is strongly imprinted in the historical data records available. The purpose of this contribution is to present a methodology capable of assessing operating rules in complex water resources systems combining historical records and expert criteria. Both sources are coupled using fuzzy logic. The procedure stages are: 1) organize expert-technicians preliminary meetings to let the first explain how they manage the system; 2) set up a fuzzy rule-based system (FRB) structure according to the way the system is managed; 3) use the historical records available to estimate the inputs' fuzzy numbers, to assign preliminary output values to the FRB rules and to train and validate these rules; 4) organize expert-technician meetings to discuss the rule structure and the input's quantification, returning if required to the second stage; 5) once the FRB structure is accepted, its output values must be refined and completed with the aid of the experts by using meetings, workshops or surveys; 6) combine the FRB with a Decision Support System (DSS) to simulate the effect of those management decisions; 7) compare its results with the ones offered by the historical records and/or simulation or optimization models; and 8) discuss with the stakeholders the model performance returning, if it's required, to the fifth or the second stage

  14. Heart Health Risk Assessment System: A Nonintrusive Proposal Using Ontologies and Expert Rules

    Directory of Open Access Journals (Sweden)

    Teresa Garcia-Valverde

    2014-01-01

    Full Text Available According to the World Health Organization, the world’s leading cause of death is heart disease, with nearly two million deaths per year. Although some factors are not possible to change, there are some keys that help to prevent heart diseases. One of the most important keys is to keep an active daily life, with moderate exercise. However, deciding what a moderate exercise is or when a slightly abnormal heart rate value is a risk depends on the person and the activity. In this paper we propose a context-aware system that is able to determine the activity the person is performing in an unobtrusive way. Then, we have defined ontology to represent the available knowledge about the person (biometric data, fitness status, medical information, etc. and her current activity (level of intensity, heart rate recommended for that activity, etc.. With such knowledge, a set of expert rules based on this ontology are involved in a reasoning process to infer levels of alerts or suggestions for the users when the intensity of the activity is detected as dangerous for her health. We show how this approach can be accomplished by using only everyday devices such as a smartphone and a smartwatch.

  15. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Directory of Open Access Journals (Sweden)

    Ujjwal Maulik

    Full Text Available Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution. The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post

  16. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Science.gov (United States)

    Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

    2015-01-01

    Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

  17. Mining association rule based on the diseases population for recommendation of medicine need

    Science.gov (United States)

    Harahap, M.; Husein, A. M.; Aisyah, S.; Lubis, F. R.; Wijaya, B. A.

    2018-04-01

    Selection of medicines that is inappropriate will lead to an empty result at medicines, this has an impact on medical services and economic value in hospital. The importance of an appropriate medicine selection process requires an automated way to select need based on the development of the patient's illness. In this study, we analyzed patient prescriptions to identify the relationship between the disease and the medicine used by the physician in treating the patient's illness. The analytical framework includes: (1) patient prescription data collection, (2) applying k-means clustering to classify the top 10 diseases, (3) applying Apriori algorithm to find association rules based on support, confidence and lift value. The results of the tests of patient prescription datasets in 2015-2016, the application of the k-means algorithm for the clustering of 10 dominant diseases significantly affects the value of trust and support of all association rules on the Apriori algorithm making it more consistent with finding association rules of disease and related medicine. The value of support, confidence and the lift value of disease and related medicine can be used as recommendations for appropriate medicine selection. Based on the conditions of disease progressions of the hospital, there is so more optimal medicine procurement.

  18. Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2018. Final rule.

    Science.gov (United States)

    2017-08-03

    This final rule updates the prospective payment rates for inpatient rehabilitation facilities (IRFs) for federal fiscal year (FY) 2018 as required by the statute. As required by section 1886(j)(5) of the Social Security Act (the Act), this rule includes the classification and weighting factors for the IRF prospective payment system's (IRF PPS) case-mix groups and a description of the methodologies and data used in computing the prospective payment rates for FY 2018. This final rule also revises the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis codes that are used to determine presumptive compliance under the "60 percent rule," removes the 25 percent payment penalty for inpatient rehabilitation facility patient assessment instrument (IRF-PAI) late transmissions, removes the voluntary swallowing status item (Item 27) from the IRF-PAI, summarizes comments regarding the criteria used to classify facilities for payment under the IRF PPS, provides for a subregulatory process for certain annual updates to the presumptive methodology diagnosis code lists, adopts the use of height/weight items on the IRF-PAI to determine patient body mass index (BMI) greater than 50 for cases of single-joint replacement under the presumptive methodology, and revises and updates measures and reporting requirements under the IRF quality reporting program (QRP).

  19. Executable specifications for hypothesis-based reasoning with Prolog and Constraint Handling Rules

    DEFF Research Database (Denmark)

    Christiansen, Henning

    2009-01-01

    Constraint Handling Rules (CHR) is an extension to Prolog which opens up a  spectrum of hypotheses-based reasoning in logic programs without additional interpretation overhead. Abduction with integrity constraints is one example of hypotheses-based reasoning which can be implemented directly...... in Prolog and CHR with a straightforward use of available and efficiently implemented facilities The present paper clarifies the semantic foundations for this way of doing abduction in CHR and Prolog as well as other examples  of hypotheses-based reasoning that is possible, including assumptive logic...

  20. Weighted Evidence Combination Rule Based on Evidence Distance and Uncertainty Measure: An Application in Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2018-01-01

    Full Text Available Conflict management in Dempster-Shafer theory (D-S theory is a hot topic in information fusion. In this paper, a novel weighted evidence combination rule based on evidence distance and uncertainty measure is proposed. The proposed approach consists of two steps. First, the weight is determined based on the evidence distance. Then, the weight value obtained in first step is modified by taking advantage of uncertainty. Our proposed method can efficiently handle high conflicting evidences with better performance of convergence. A numerical example and an application based on sensor fusion in fault diagnosis are given to demonstrate the efficiency of our proposed method.

  1. Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

    Science.gov (United States)

    DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

    2016-01-01

    Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

  2. Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

    Science.gov (United States)

    DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

    2016-01-01

    Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

  3. [Study on Ammonia Emission Rules in a Dairy Feedlot Based on Laser Spectroscopy Detection Method].

    Science.gov (United States)

    He, Ying; Zhang, Yu-jun; You, Kun; Wang, Li-ming; Gao, Yan-wei; Xu, Jin-feng; Gao, Zhi-ling; Ma, Wen-qi

    2016-03-01

    It needs on-line monitoring of ammonia concentration on dairy feedlot to disclose ammonia emissions characteristics accurately for reducing ammonia emissions and improving the ecological environment. The on-line monitoring system for ammonia concentration has been designed based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology combining with long open-path technology, then the study has been carried out with inverse dispersion technique and the system. The ammonia concentration in-situ has been detected and ammonia emission rules have been analyzed on a dairy feedlot in Baoding in autumn and winter of 2013. The monitoring indicated that the peak of ammonia concentration was 6.11 x 10(-6) in autumn, and that was 6.56 x 10(-6) in winter. The concentration results show that the variation of ammonia concentration had an obvious diurnal periodicity, and the general characteristic of diurnal variation was that the concentration was low in the daytime and was high at night. The ammonia emissions characteristic was obtained with inverse dispersion model that the peak of ammonia emissions velocity appeared at noon. The emission velocity was from 1.48 kg/head/hr to 130.6 kg/head/hr in autumn, and it was from 0.004 5 kg/head/hr to 43.32 kg/head/hr in winter which was lower than that in autumn. The results demonstrated ammonia emissions had certain seasonal differences in dairy feedlot scale. In conclusion, the ammonia concentration was detected with optical technology, and the ammonia emissions results were acquired by inverse dispersion model analysis with large range, high sensitivity, quick response without gas sampling. Thus, it's an effective method for ammonia emissions monitoring in dairy feedlot that provides technical support for scientific breeding.

  4. EPICS based DAQ system

    International Nuclear Information System (INIS)

    Cheng Weixing; Chen Yongzhong; Zhou Weimin; Ye Kairong; Liu Dekang

    2002-01-01

    EPICS is the most popular developing platform to build control system and beam diagnostic system in modern physics experiment facilities. An EPICS based data acquisition system was built in Redhat 6.2 operation system. The system is successfully used in the beam position monitor mapping, it improves the mapping process a lot

  5. TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries.

    Science.gov (United States)

    Chang, Yung-Chun; Dai, Hong-Jie; Wu, Johnny Chi-Yang; Chen, Jian-Ming; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

    2013-12-01

    Patient discharge summaries provide detailed medical information about individuals who have been hospitalized. To make a precise and legitimate assessment of the abundant data, a proper time layout of the sequence of relevant events should be compiled and used to drive a patient-specific timeline, which could further assist medical personnel in making clinical decisions. The process of identifying the chronological order of entities is called temporal relation extraction. In this paper, we propose a hybrid method to identify appropriate temporal links between a pair of entities. The method combines two approaches: one is rule-based and the other is based on the maximum entropy model. We develop an integration algorithm to fuse the results of the two approaches. All rules and the integration algorithm are formally stated so that one can easily reproduce the system and results. To optimize the system's configuration, we used the 2012 i2b2 challenge TLINK track dataset and applied threefold cross validation to the training set. Then, we evaluated its performance on the training and test datasets. The experiment results show that the proposed TEMPTING (TEMPoral relaTion extractING) system (ranked seventh) achieved an F-score of 0.563, which was at least 30% better than that of the baseline system, which randomly selects TLINK candidates from all pairs and assigns the TLINK types. The TEMPTING system using the hybrid method also outperformed the stage-based TEMPTING system. Its F-scores were 3.51% and 0.97% better than those of the stage-based system on the training set and test set, respectively. Copyright © 2013 Elsevier Inc. All rights reserved.

  6. Robust Management of Combined Heat and Power Systems via Linear Decision Rules

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Madsen, Henrik

    2014-01-01

    The heat and power outputs of Combined Heat and Power (CHP) units are jointly constrained. Hence, the optimal management of systems including CHP units is a multicommodity optimization problem. Problems of this type are stochastic, owing to the uncertainty inherent both in the demand for heat and...... linear decision rules to guarantee both tractability and a correct representation of the dynamic aspects of the problem. Numerical results from an illustrative example confirm the value of the proposed approach....

  7. Neural Substrates of Similarity and Rule-based Strategies in Judgment

    Directory of Open Access Journals (Sweden)

    Bettina eVon Helversen

    2014-10-01

    Full Text Available Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI, we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved.

  8. A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

    Directory of Open Access Journals (Sweden)

    H. Y. Gu

    2017-09-01

    Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

  9. PENGEMBANGAN SISTEM EVALUASI DESAIN PRODUK BERBASIS ROTAN DENGAN PENDEKATAN REKAYASA KANSEI DAN ASSOCIATION RULES SYSTEM

    OpenAIRE

    Vonny Setiaries Johan; Sapta Rahardja; E Gumbira Said; Taufik Djatna

    2016-01-01

    In product development, it is very important for manufacturers to find out what the customer wants from the product. On the other hand, manufacturers do not know clearly about what the customer wants from the product. This study proposes an evaluation method of product design using Kansei engineering methods and association rules approach. Using rattan dining chair as the object, the chair design divided into five elements, which are backrest, seat, armrest, base and woven. In this study, Kan...

  10. Technique Based on Image Pyramid and Bayes Rule for Noise Reduction in Unsupervised Change Detection

    Institute of Scientific and Technical Information of China (English)

    LI Zhi-qiang; HUO hong; FANG Tao; ZHU Ju-lian; GE Wei-li

    2009-01-01

    In this paper, a technique based on image pyramid and Bayes rule for reducing noise effects in unsupervised change detection is proposed. By using Gaussian pyramid to process two multitemporal images respectively, two image pyramids are constructed. The difference pyramid images are obtained by point-by-point subtraction between the same level images of the two image pyramids. By resizing all difference pyramid images to the size of the original multitemporal image and then making product operator among them, a map being similar to the difference image is obtained. The difference image is generated by point-by-point subtraction between the two multitemporal images directly. At last, the Bayes rule is used to distinguish the changed pixels. Both synthetic and real data sets are used to evaluate the performance of the proposed technique. Experimental results show that the map from the proposed technique is more robust to noise than the difference image.

  11. A rough set-based association rule approach implemented on a brand trust evaluation model

    Science.gov (United States)

    Liao, Shu-Hsien; Chen, Yin-Ju

    2017-09-01

    In commerce, businesses use branding to differentiate their product and service offerings from those of their competitors. The brand incorporates a set of product or service features that are associated with that particular brand name and identifies the product/service segmentation in the market. This study proposes a new data mining approach, a rough set-based association rule induction, implemented on a brand trust evaluation model. In addition, it presents as one way to deal with data uncertainty to analyse ratio scale data, while creating predictive if-then rules that generalise data values to the retail region. As such, this study uses the analysis of algorithms to find alcoholic beverages brand trust recall. Finally, discussions and conclusion are presented for further managerial implications.

  12. Orthogonal search-based rule extraction for modelling the decision to transfuse.

    Science.gov (United States)

    Etchells, T A; Harrison, M J

    2006-04-01

    Data from an audit relating to transfusion decisions during intermediate or major surgery were analysed to determine the strengths of certain factors in the decision making process. The analysis, using orthogonal search-based rule extraction (OSRE) from a trained neural network, demonstrated that the risk of tissue hypoxia (ROTH) assessed using a 100-mm visual analogue scale, the haemoglobin value (Hb) and the presence or absence of on-going haemorrhage (OGH) were able to reproduce the transfusion decisions with a joint specificity of 0.96 and sensitivity of 0.93 and a positive predictive value of 0.9. The rules indicating transfusion were: 1. ROTH > 32 mm and Hb 13 mm and Hb 38 mm, Hb < 102 g x l(-1) and OGH; 4. Hb < 78 g x l(-1).

  13. Tuning rules for robust FOPID controllers based on multi-objective optimization with FOPDT models.

    Science.gov (United States)

    Sánchez, Helem Sabina; Padula, Fabrizio; Visioli, Antonio; Vilanova, Ramon

    2017-01-01

    In this paper a set of optimally balanced tuning rules for fractional-order proportional-integral-derivative controllers is proposed. The control problem of minimizing at once the integrated absolute error for both the set-point and the load disturbance responses is addressed. The control problem is stated as a multi-objective optimization problem where a first-order-plus-dead-time process model subject to a robustness, maximum sensitivity based, constraint has been considered. A set of Pareto optimal solutions is obtained for different normalized dead times and then the optimal balance between the competing objectives is obtained by choosing the Nash solution among the Pareto-optimal ones. A curve fitting procedure has then been applied in order to generate suitable tuning rules. Several simulation results show the effectiveness of the proposed approach. Copyright © 2016. Published by Elsevier Ltd.

  14. Establishment of ''Internal Rules'' and EDMS - Electronic Document Management System at NPP NEK

    International Nuclear Information System (INIS)

    Mandic, D.

    2012-01-01

    The main purpose of this paper is to present NPP's plans regarding the on-going project that started in November 2011, and that is related to the establishment of ''Internal Rules'' and EDMS - Electronic Document Management System.The term ''Internal Rules'' has been directly translated from Slovenian language (''Notranja pravila'') and adopted from the translated version of appropriate Slovenian national codes (ZVDAGA [1] in Slovenian language or PDAAIA [2] in English version). ''Internal Rules on capture and storage of materials in digital form'' refer to the rules adopted by a person as his/her internal act with reference to storage of his/her material. The main purpose for the establishment of the Internal Rules is to be able to justify that Krsko NPP is organized in compliance with the national codes covering that subject and strictly performing according to those Internal Rules. Once a Slovenian company achieves recognized and registered status in accordance with the Internal Rules document that has been certified and approved by the ARS (Archives of the Republic Slovenia), such company can utilize e-documents in the same way as they would utilize physical documents. Furthermore, a Slovenian company with approved Internal Rules can use e-documents in any legal aspect associated with the document's life cycle and the document's content as they would use the physical document or an authorized and approved copy of the physical document. Related to the nuclear regulatory background, NEK operates in compliance with the Slovenian legislation and also the US codes, regulations and guidelines; therefore, regarding the NPP specific documents, the Internal Rules and EDMS must also be in compliance with them. Since early 1990's, NEK has implemented document/records management system oriented towards supporting storage and management of physical documents/records and controlling distribution of active document copies. Document/records management system was supported by

  15. Toward Sensor-Based Context Aware Systems

    Directory of Open Access Journals (Sweden)

    Kouhei Takada

    2012-01-01

    Full Text Available This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.

  16. An Investigation of Care-Based vs. Rule-Based Morality in Frontotemporal Dementia, Alzheimer’s Disease, and Healthy Controls

    Science.gov (United States)

    Carr, Andrew R.; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S.; Mather, Michelle; Jimenez, Elvira E.; Thompson, Paul; Mendez, Mario F.

    2015-01-01

    Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer’s disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. PMID:26432341

  17. Paper Improving Rule Based Stemmers to Solve Some Special Cases of Arabic Language

    Directory of Open Access Journals (Sweden)

    Soufiane Farrah

    2017-04-01

    Full Text Available Analysis of Arabic language has become a necessity because of its big evolution; we propose in this paper a rule based extraction method of Arabic text to solve some weaknesses founded on previous research works. Our approach is divided on preprocessing phase, on which we proceed to the tokenization of the text, and formatting it by removing any punctuation, diacritics and non-letter characters. Treatment phase based on the elimination of several sets of affixes (diacritics, prefixes, and suffixes, and on the application of several patterns. A check phase that verifies if the root extracted is correct, by searching the result in root dictionaries.

  18. The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning.

    Directory of Open Access Journals (Sweden)

    Abe D Hofman

    Full Text Available We propose and test three statistical models for the analysis of children's responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779, and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808. For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development.

  19. Assessment of the Degree of Consistency of the System of Fuzzy Rules

    Directory of Open Access Journals (Sweden)

    Pospelova Lyudmila Yakovlevna

    2013-12-01

    Full Text Available The article analyses recent achievements and publications and shows that difficulties of explaining the nature of fuzziness and equivocation arise in socio-economic models that use the traditional paradigm of classical rationalism (computational, agent and econometric models. The accumulated collective experience of development of optimal models confirms prospectiveness of application of the fuzzy set approach in modelling the society. The article justifies the necessity of study of the nature of inconsistency in fuzzy knowledge bases both on the generalised ontology level and on pragmatic functional level of the logical inference. The article offers the method of search for logical and conceptual contradictions in the form of a combination of the abduction and modus ponens. It discusses the key issue of the proposed method: what properties should have the membership function of the secondary fuzzy set, which describes in fuzzy inference models such a resulting state of the object of management, which combines empirically incompatible properties with high probability. The degree of membership of the object of management in several incompatible classes with respect to the fuzzy output variable is the degree of fuzziness of the “Intersection of all results of the fuzzy inference of the set, applied at some input of rules, is an empty set” statement. The article describes an algorithm of assessment of the degree of consistency. It provides an example of the step-by-step detection of contradictions in statistical fuzzy knowledge bases at the pragmatic functional level of the logical output. The obtained results of testing in the form of sets of incompatible facts, output chains, sets of non-crossing intervals and computed degrees of inconsistency allow experts timely elimination of inadmissible contradictions and, at the same time, increase of quality of recommendations and assessment of fuzzy expert systems.

  20. Situation-assessment and decision-aid production-rule analysis system for nuclear plant monitoring and emergency preparedness

    International Nuclear Information System (INIS)

    Gvillo, D.; Ragheb, M.; Parker, M.; Swartz, S.

    1987-01-01

    A Production-Rule Analysis System is developed for Nuclear Plant Monitoring. The signals generated by the Zion-1 Plant are considered. A Situation-Assessment and Decision-Aid capability is provided for monitoring the integrity of the Plant Radiation, the Reactor Coolant, the Fuel Clad, and the Containment Systems. A total of 41 signals are currently fed as facts to an Inference Engine functioning in the backward-chaining mode and built along the same structure as the E-Mycin system. The Goal-Tree constituting the Knowledge Base was generated using a representation in the form of Fault Trees deduced from plant procedures information. The system is constructed in support of the Data Analysis and Emergency Preparedness tasks at the Illinois Radiological Emergency Assessment Center (REAC)

  1. Situation-Assessment And Decision-Aid Production-Rule Analysis System For Nuclear Plant Monitoring And Emergency Preparedness

    Science.gov (United States)

    Gvillo, D.; Ragheb, M.; Parker, M.; Swartz, S.

    1987-05-01

    A Production-Rule Analysis System is developed for Nuclear Plant Monitoring. The signals generated by the Zion-1 Plant are considered. A Situation-Assessment and Decision-Aid capability is provided for monitoring the integrity of the Plant Radiation, the Reactor Coolant, the Fuel Clad, and the Containment Systems. A total of 41 signals are currently fed as facts to an Inference Engine functioning in the backward-chaining mode and built along the same structure as the E-Mycin system. The Goal-Tree constituting the Knowledge Base was generated using a representation in the form of Fault Trees deduced from plant procedures information. The system is constructed in support of the Data Analysis and Emergency Preparedness tasks at the Illinois Radiological Emergency Assessment Center (REAC).

  2. Effects of Memorization of Rule Statements on Acquisition and Retention of Rule-Governed Behavior in a Computer-Based Learning Task.

    Science.gov (United States)

    Towle, Nelson J.

    One hundred and twenty-four high school students were randomly assigned to four groups: 33 subjects memorized the rule statement before, 29 subjects memorized the rule statement during, and 30 subjects memorized the rule statement after instruction in rule application skills. Thirty-two subjects were not required to memorize rule statements.…

  3. Scalable rule-based modelling of allosteric proteins and biochemical networks.

    Directory of Open Access Journals (Sweden)

    Julien F Ollivier

    2010-11-01

    Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

  4. The rule of law

    Directory of Open Access Journals (Sweden)

    Besnik Murati

    2015-07-01

    Full Text Available The state as an international entity and its impact on the individual’s right has been and still continues to be a crucial factor in the relationship between private and public persons. States vary in terms of their political system, however, democratic states are based on the separation of powers and human rights within the state. Rule of law is the product of many actors in a state, including laws, individuals, society, political system, separation of powers, human rights, the establishment of civil society, the relationship between law and the individual, as well as, individual-state relations. Purpose and focus of this study is the importance of a functioning state based on law, characteristics of the rule of law, separation of powers and the basic concepts of the rule of law.

  5. Reduction rules-based search algorithm for opportunistic replacement strategy of multiple life-limited parts

    Directory of Open Access Journals (Sweden)

    Xuyun FU

    2018-01-01

    Full Text Available The opportunistic replacement of multiple Life-Limited Parts (LLPs is a problem widely existing in industry. The replacement strategy of LLPs has a great impact on the total maintenance cost to a lot of equipment. This article focuses on finding a quick and effective algorithm for this problem. To improve the algorithm efficiency, six reduction rules are suggested from the perspectives of solution feasibility, determination of the replacement of LLPs, determination of the maintenance occasion and solution optimality. Based on these six reduction rules, a search algorithm is proposed. This search algorithm can identify one or several optimal solutions. A numerical experiment shows that these six reduction rules are effective, and the time consumed by the algorithm is less than 38 s if the total life of equipment is shorter than 55000 and the number of LLPs is less than 11. A specific case shows that the algorithm can obtain optimal solutions which are much better than the result of the traditional method in 10 s, and it can provide support for determining to-be-replaced LLPs when determining the maintenance workscope of an aircraft engine. Therefore, the algorithm is applicable to engineering applications concerning opportunistic replacement of multiple LLPs in aircraft engines.

  6. Analysis of QCD sum rule based on the maximum entropy method

    International Nuclear Information System (INIS)

    Gubler, Philipp

    2012-01-01

    QCD sum rule was developed about thirty years ago and has been used up to the present to calculate various physical quantities like hadrons. It has been, however, needed to assume 'pole + continuum' for the spectral function in the conventional analyses. Application of this method therefore came across with difficulties when the above assumption is not satisfied. In order to avoid this difficulty, analysis to make use of the maximum entropy method (MEM) has been developed by the present author. It is reported here how far this new method can be successfully applied. In the first section, the general feature of the QCD sum rule is introduced. In section 2, it is discussed why the analysis by the QCD sum rule based on the MEM is so effective. In section 3, the MEM analysis process is described, and in the subsection 3.1 likelihood function and prior probability are considered then in subsection 3.2 numerical analyses are picked up. In section 4, some cases of applications are described starting with ρ mesons, then charmoniums in the finite temperature and finally recent developments. Some figures of the spectral functions are shown. In section 5, summing up of the present analysis method and future view are given. (S. Funahashi)

  7. PENGEMBANGAN SISTEM EVALUASI DESAIN PRODUK BERBASIS ROTAN DENGAN PENDEKATAN REKAYASA KANSEI DAN ASSOCIATION RULES SYSTEM

    Directory of Open Access Journals (Sweden)

    Vonny Setiaries Johan

    2016-11-01

    Full Text Available In product development, it is very important for manufacturers to find out what the customer wants from the product. On the other hand, manufacturers do not know clearly about what the customer wants from the product. This study proposes an evaluation method of product design using Kansei engineering methods and association rules approach. Using rattan dining chair as the object, the chair design divided into five elements, which are backrest, seat, armrest, base and woven. In this study, Kansei words from customers such as beautiful, unique, innovative, comfortable, natural, modern, sturdy and simple can be translated in to element design.   Using the support and confidence values, if-then rules can be used as the basis for the assessment of rattan dining chairs

  8. ALPHABET SIGN LANGUAGE RECOGNITION USING LEAP MOTION TECHNOLOGY AND RULE BASED BACKPROPAGATION-GENETIC ALGORITHM NEURAL NETWORK (RBBPGANN

    Directory of Open Access Journals (Sweden)

    Wijayanti Nurul Khotimah

    2017-01-01

    Full Text Available Sign Language recognition was used to help people with normal hearing communicate effectively with the deaf and hearing-impaired. Based on survey that conducted by Multi-Center Study in Southeast Asia, Indonesia was on the top four position in number of patients with hearing disability (4.6%. Therefore, the existence of Sign Language recognition is important. Some research has been conducted on this field. Many neural network types had been used for recognizing many kinds of sign languages. However, their performance are need to be improved. This work focuses on the ASL (Alphabet Sign Language in SIBI (Sign System of Indonesian Language which uses one hand and 26 gestures. Here, thirty four features were extracted by using Leap Motion. Further, a new method, Rule Based-Backpropagation Genetic Al-gorithm Neural Network (RB-BPGANN, was used to recognize these Sign Languages. This method is combination of Rule and Back Propagation Neural Network (BPGANN. Based on experiment this pro-posed application can recognize Sign Language up to 93.8% accuracy. It was very good to recognize large multiclass instance and can be solution of overfitting problem in Neural Network algorithm.

  9. Rule representation using linked data technologies

    NARCIS (Netherlands)

    Zhang, C.; Beetz, J.

    2016-01-01

    In this paper, we report a prototype rule checking system based on Semantic Web and Linked Data technologies. This research aims to find a method to represent rules outside of specific systems, and can be used to integrate and share them among different organizations. In this system we propose to

  10. Use of negotiated rulemaking in developing technical rules for low-Earth orbit mobile satellite systems

    Science.gov (United States)

    Taylor, Leslie A.

    Technical innovations have converged with the exploding market demand for mobile telecommunications to create the impetus for low-earth orbit (LEO) communications satellite systems. The so-called 'Little LEO's' propose use of VHF and UHF spectrum to provide position - location and data messaging services. The so-called 'Big LEO's' propose to utilize the RDSS bands to provide voice and data services. In the United States, several applications were filed with the U.S. Federal Communications Commission (FCC) to construct and operate these mobile satellite systems. To enable the prompt introduction of such new technology services, the FCC is using innovative approaches to process the applications. Traditionally, when the FCC is faced with 'mutually exclusive' applications, e.g. a grant of one would preclude a grant of the others, it uses selection mechanisms such as comparative hearings or lotteries. In the case of the LEO systems, the FCC has sought to avoid these time-consuming approaches by using negotiated rulemakings. The FCC's objective is to enable the multiple applicants and other interested parties to agree on technical and service rules which will enable the grant of all qualified applications. With regard to the VHF/UHF systems, the Advisory Committee submitted a consensus report to the FCC. The process for the systems operating in the bands above 1 GHz involved more parties and more issues but still provided the FCC useful technical information to guide the adoption of rules for the new mobile satellite service.

  11. Hydrogel based occlusion systems

    NARCIS (Netherlands)

    Stam, F.A.; Jackson, N.; Dubruel, P.; Adesanya, K.; Embrechts, A.; Mendes, E.; Neves, H.P.; Herijgers, P.; Verbrugghe, Y.; Shacham, Y.; Engel, L.; Krylov, V.

    2013-01-01

    A hydrogel based occlusion system, a method for occluding vessels, appendages or aneurysms, and a method for hydrogel synthesis are disclosed. The hydrogel based occlusion system includes a hydrogel having a shrunken and a swollen state and a delivery tool configured to deliver the hydrogel to a

  12. Compensatory Processing During Rule-Based Category Learning in Older Adults

    Science.gov (United States)

    Bharani, Krishna L.; Paller, Ken A.; Reber, Paul J.; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G.

    2016-01-01

    Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex. PMID:26422522

  13. Exposure estimates based on broadband elf magnetic field measurements versus the ICNIRP multiple frequency rule

    International Nuclear Information System (INIS)

    Paniagua, Jesus M.; Rufo, Montana; Jimenez, Antonio; Pachon, Fernando T.; Carrero, Julian

    2015-01-01

    The evaluation of exposure to extremely low-frequency (ELF) magnetic fields using broadband measurement techniques gives satisfactory results when the field has essentially a single frequency. Nevertheless, magnetic fields are in most cases distorted by harmonic components. This work analyses the harmonic components of the ELF magnetic field in an outdoor urban context and compares the evaluation of the exposure based on broadband measurements with that based on spectral analysis. The multiple frequency rule of the International Commission on Non-ionizing Radiation Protection (ICNIRP) regulatory guidelines was applied. With the 1998 ICNIRP guideline, harmonics dominated the exposure with a 55 % contribution. With the 2010 ICNIRP guideline, however, the primary frequency dominated the exposure with a 78 % contribution. Values of the exposure based on spectral analysis were significantly higher than those based on broadband measurements. Hence, it is clearly necessary to determine the harmonic components of the ELF magnetic field to assess exposure in urban contexts. (authors)

  14. Typelets - a rule-based evaluation model for dynamic, statically typed user interfaces

    DEFF Research Database (Denmark)

    Elsman, Martin; Schack-Nielsen, Anders

    2014-01-01

    We present the concept of typelets, a specification technique for dynamic graphical user interfaces (GUIs) based on types. The technique is implemented in a dialect of ML, called MLFi (MLFi is a derivative of OCaml, extended by LexiFi with extensions targeted at the financial industry), which...... specification language allows layout programmers (e.g., end-users) to reorganize layouts in a type-safe way without being allowed to alter the rule machinery. The resulting framework is highly flexible and allows for creating highly maintainable modules. It is used with success in the context of SimCorp's high...

  15. Fuzzy rule-based forecast of meteorological drought in western Niger

    Science.gov (United States)

    Abdourahamane, Zakari Seybou; Acar, Reşat

    2018-01-01

    Understanding the causes of rainfall anomalies in the West African Sahel to effectively predict drought events remains a challenge. The physical mechanisms that influence precipitation in this region are complex, uncertain, and imprecise in nature. Fuzzy logic techniques are renowned to be highly efficient in modeling such dynamics. This paper attempts to forecast meteorological drought in Western Niger using fuzzy rule-based modeling techniques. The 3-month scale standardized precipitation index (SPI-3) of four rainfall stations was used as predictand. Monthly data of southern oscillation index (SOI), South Atlantic sea surface temperature (SST), relative humidity (RH), and Atlantic sea level pressure (SLP), sourced from the National Oceanic and Atmosphere Administration (NOAA), were used as predictors. Fuzzy rules and membership functions were generated using fuzzy c-means clustering approach, expert decision, and literature review. For a minimum lead time of 1 month, the model has a coefficient of determination R 2 between 0.80 and 0.88, mean square error (MSE) below 0.17, and Nash-Sutcliffe efficiency (NSE) ranging between 0.79 and 0.87. The empirical frequency distributions of the predicted and the observed drought classes are equal at the 99% of confidence level based on two-sample t test. Results also revealed the discrepancy in the influence of SOI and SLP on drought occurrence at the four stations while the effect of SST and RH are space independent, being both significantly correlated (at α based forecast model shows better forecast skills.

  16. Study on Transfer Rules of Coal Reservoir Pressure Drop Based on Coalbed Methane Well Drainage Experiments

    Science.gov (United States)

    Yuhang, X.

    2017-12-01

    A pumping test was carried out to explore the transfer rules of pressure drop in coal reservoir during the drainage. The experiment was divided into three stages. In the first stage, the pump displacement of 3m3/h was used to reduce the bottom hole flowing pressure and stopped until the continuous gas phase was produced; Undertaking the first stage, in the second stage, when the gas phase was continuously produced, the pump was stopped immediately. As the bottom hole flowing pressure going up without gas phase, pumping started again for a week. In the third stage ,the well pumping was carried out at the bottom hole pressure drop rate of 30Kpa/d after two months' recovery. Combined with the data of regional geology and fractured well, taking the characteristics of macroscopic coal rocks, development of pore and fracture in coal and isothermal adsorption test as the background, the features of reservoir output in each stage of the experiment were analyzed and compared, and then the transfer rules of pressure drop contained in the differences of the output was studied further. In the first and third stage of the experiment, the output of liquid phase was much larger than the space volume of coal reservoir pore and fracture in the range of 100m2. In the second stage, the output of the continuous gas phase appeared around 0.7Mpa when the continuous gas phase appears below the critical desorption pressure of 0.25Mpa during the whole experiment. The results indicate that, the transfer of pressure drop in the coal reservoir of this well is mainly horizontal, and the liquid phase produced in the reservoir mainly comes from the recharge of the reservoir at the far end of the relative high pressure area; the adsorption space of coalbed methane in the coal matrix as well as the main migration channel of fluid in the reservoir doesn't belong to the same pressure system and there exists the communication barrier between them. In addition, the increasing of the effective stress

  17. Rule-Based Reasoning Is Fast and Belief-Based Reasoning Can Be Slow: Challenging Current Explanations of Belief-Bias and Base-Rate Neglect

    Science.gov (United States)

    Newman, Ian R.; Gibb, Maia; Thompson, Valerie A.

    2017-01-01

    It is commonly assumed that belief-based reasoning is fast and automatic, whereas rule-based reasoning is slower and more effortful. Dual-Process theories of reasoning rely on this speed-asymmetry explanation to account for a number of reasoning phenomena, such as base-rate neglect and belief-bias. The goal of the current study was to test this…

  18. An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis

    Directory of Open Access Journals (Sweden)

    De Zhao

    2018-01-01

    Full Text Available Smart card data provide valuable insights and massive samples for enhancing the understanding of transfer behavior between metro and public bicycle. However, smart cards for metro and public bicycle are often issued and managed by independent companies and this results in the same commuter having different identity tags in the metro and public bicycle smart card systems. The primary objective of this study is to develop a data fusion methodology for matching metro and public bicycle smart cards for the same commuter using historical smart card data. A novel method with association rules to match the data derived from the two systems is proposed and validation was performed. The results showed that our proposed method successfully matched 573 pairs of smart cards with an accuracy of 100%. We also validated the association rules method through visualization of individual metro and public bicycle trips. Based on the matched cards, interesting findings of metro-bicycle transfer have been derived, including the spatial pattern of the public bicycle as first/last mile solution as well as the duration of a metro trip chain.

  19. Automated biometric access control system for two-man-rule enforcement

    International Nuclear Information System (INIS)

    Holmes, J.P.; Maxwell, R.L.; Henderson, R.W.

    1991-01-01

    This paper describes a limited access control system for nuclear facilities which makes use of the eye retinal identity verifier to control the passage of personnel into and out of one or a group of security controlled working areas. This access control system requires no keys, cards or credentials. The user simply enters his Personal Identification Number (PIN) and takes an eye reading to request passage. The PIN does not have to be kept secret. The system then relies on biometric identity verification of the user, along with other system information, to make the decision of whether or not to unlock the door. It also enforces multiple zones control with personnel tracking and the two-man-rule

  20. Autonomous Rule Creation for Intrusion Detection

    Energy Technology Data Exchange (ETDEWEB)

    Todd Vollmer; Jim Alves-Foss; Milos Manic

    2011-04-01

    Many computational intelligence techniques for anomaly based network intrusion detection can be found in literature. Translating a newly discovered intrusion recognition criteria into a distributable rule can be a human intensive effort. This paper explores a multi-modal genetic algorithm solution for autonomous rule creation. This algorithm focuses on the process of creating rules once an intrusion has been identified, rather than the evolution of rules to provide a solution for intrusion detection. The algorithm was demonstrated on anomalous ICMP network packets (input) and Snort rules (output of the algorithm). Output rules were sorted according to a fitness value and any duplicates were removed. The experimental results on ten test cases demonstrated a 100 percent rule alert rate. Out of 33,804 test packets 3 produced false positives. Each test case produced a minimum of three rule variations that could be used as candidates for a production system.

  1. Criterial noise effects on rule-based category learning: the impact of delayed feedback.

    Science.gov (United States)

    Ell, Shawn W; Ing, A David; Maddox, W Todd

    2009-08-01

    Variability in the representation of the decision criterion is assumed in many category-learning models, yet few studies have directly examined its impact. On each trial, criterial noise should result in drift in the criterion and will negatively impact categorization accuracy, particularly in rule-based categorization tasks, where learning depends on the maintenance and manipulation of decision criteria. In three experiments, we tested this hypothesis and examined the impact of working memory on slowing the drift rate. In Experiment 1, we examined the effect of drift by inserting a 5-sec delay between the categorization response and the delivery of corrective feedback, and working memory demand was manipulated by varying the number of decision criteria to be learned. Delayed feedback adversely affected performance, but only when working memory demand was high. In Experiment 2, we built on a classic finding in the absolute identification literature and demonstrated that distributing the criteria across multiple dimensions decreases the impact of drift during the delay. In Experiment 3, we confirmed that the effect of drift during the delay is moderated by working memory. These results provide important insights into the interplay between criterial noise and working memory, as well as providing important constraints for models of rule-based category learning.

  2. Experimental test of Neel's theory of the Rayleigh rule using gradually devitrified Co-based glass

    International Nuclear Information System (INIS)

    Lachowicz, H.K.

    2000-01-01

    It is shown that gradually devitrified Co-based nonmagnetostrictive metallic glass is an excellent model material to verify Louis Neel's theory of the Rayleigh rule. In the course of the calculations, Neel showed that the parameter p=bH c /a (where H c is the coercivity, a and b are the coefficients of a quadratic polynomial expressing the Rayleigh rule) is expected to range between 0.6 (hard magnets) and 1.6 (soft). However, the experimental values of this parameter, reported in the literature for a number of mono- and poly-crystalline magnets, are much greater than those expected from the theory presented by Neel (in some cases even by two orders of magnitude). The measurements, performed for a series of Co-based metallic glass samples annealed at gradually increasing temperature to produce nanocrystalline structures with differentiated density and size of the crystallites, have shown that the calculated values of the parameter p fall within the range expected from Neel's theory

  3. A rule-based industrial boiler selection system

    NARCIS (Netherlands)

    Tan, C.F.; Khalil, S.N.; Karjanto, J.; Tee, B.T.; Wahidin, L.S.; Chen, W.; Rauterberg, G.W.M.; Sivarao, S.; Lim, T.L.

    2015-01-01

    Boiler is a device used for generating the steam for power generation, process use or heating, and hot water for heating purposes. Steam boiler consists of the containing vessel and convection heating surfaces only, whereas a steam generator covers the whole unit, encompassing water wall tubes,

  4. Online Rule Generation Software Process Model

    OpenAIRE

    Sudeep Marwaha; Alka Aroa; Satma M C; Rajni Jain; R C Goyal

    2013-01-01

    For production systems like expert systems, a rule generation software can facilitate the faster deployment. The software process model for rule generation using decision tree classifier refers to the various steps required to be executed for the development of a web based software model for decision rule generation. The Royce’s final waterfall model has been used in this paper to explain the software development process. The paper presents the specific output of various steps of modified wat...

  5. Design and Implementation an Autonomous Humanoid Robot Based on Fuzzy Rule-Based Motion Controller

    Directory of Open Access Journals (Sweden)

    Mohsen Taheri

    2010-04-01

    Full Text Available Research on humanoid robotics in Mechatronics and Automation Laboratory, Electrical and Computer Engineering, Islamic Azad University Khorasgan branch (Isfahan of Iran was started at
    the beginning of this decade. Various research prototypes for humanoid robots have been designed and are going through evolution over these years. This paper describes the hardware and software design of the kid size humanoid robot systems of the PERSIA Team in 2009. The robot has 20 actuated degrees of freedom based on Hitec HSR898. In this paper we have tried to focus on areas such as mechanical structure, Image processing unit, robot controller, Robot AI and behavior
    learning. In 2009, our developments for the Kid size humanoid robot include: (1 the design and construction of our new humanoid robots (2 the design and construction of a new hardware and software controller to be used in our robots. The project is described in two main parts: Hardware and Software. The software is developed a robot application which consists walking controller, autonomous motion robot, self localization base on vision and Particle Filter, local AI, Trajectory Planning, Motion Controller and Network. The hardware consists of the mechanical structure and the driver circuit board. Each robot is able to walk, fast walk, pass, kick and dribble when it catches
    the ball. These humanoids have been successfully participating in various robotic soccer competitions. This project is still in progress and some new interesting methods are described in the current report.

  6. Increasing Supply-Chain Visibility with Rule-Based RFID Data Analysis

    DEFF Research Database (Denmark)

    Ilic, A.; Andersen, Thomas; Michahelles, F.

    2009-01-01

    RFID technology tracks the flow of physical items and goods in supply chains to help users detect inefficiencies, such as shipment delays, theft, or inventory problems. An inevitable consequence, however, is that it generates huge numbers of events. To exploit these large amounts of data, the Sup......RFID technology tracks the flow of physical items and goods in supply chains to help users detect inefficiencies, such as shipment delays, theft, or inventory problems. An inevitable consequence, however, is that it generates huge numbers of events. To exploit these large amounts of data......, the Supply Chain Visualizer increases supply-chain visibility by analyzing RFID data, using a mix of automated analysis techniques and human effort. The tool's core concepts include rule-based analysis techniques and a map-based representation interface. With these features, it lets users visualize...

  7. Design of Racing Electric Control System Based on AVR SCM

    Directory of Open Access Journals (Sweden)

    Shuang WAN

    2014-10-01

    Full Text Available A racing car’s instrument system, signal system and monitoring system were designed based on the rules of the competition (FSAE, Formula SAE. The main components of the instrument system were selected by comparing the advantages and disadvantages of various instrument systems. And the circuit diagram and PCB diagram of the instrument system was drawn by Altium Designer. Then, the instrument system with Single Chip Microcomputer (SCM as the main body was set up according to the circuit diagram. Besides, programs were written according to the function of instrument system. Finally, the instrument system was debugged. In the aspect of the design of signal system and monitoring system, the circuit diagram of signal system and signal system were drawn according to the racing design requirements and rules. Currently, the instrument system has been successfully debugged. And the design of circuit diagram of signal system and monitoring system has been completed.

  8. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    Directory of Open Access Journals (Sweden)

    Hurwitz Eric L

    2008-08-01

    Full Text Available Abstract Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source and 3 (which investigates perpetuating factors of the pain experience. In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed.

  9. Residents' surgical performance during the laboratory years: an analysis of rule-based errors.

    Science.gov (United States)

    Nathwani, Jay N; Wise, Brett J; Garren, Margaret E; Mohamadipanah, Hossein; Van Beek, Nicole; DiMarco, Shannon M; Pugh, Carla M

    2017-11-01

    Nearly one-third of surgical residents will enter into academic development during their surgical residency by dedicating time to a research fellowship for 1-3 y. Major interest lies in understanding how laboratory residents' surgical skills are affected by minimal clinical exposure during academic development. A widely held concern is that the time away from clinical exposure results in surgical skills decay. This study examines the impact of the academic development years on residents' operative performance. We hypothesize that the use of repeated, annual assessments may result in learning even without individual feedback on participants simulated performance. Surgical performance data were collected from laboratory residents (postgraduate years 2-5) during the summers of 2014, 2015, and 2016. Residents had 15 min to complete a shortened, simulated laparoscopic ventral hernia repair procedure. Final hernia repair skins from all participants were scored using a previously validated checklist. An analysis of variance test compared the mean performance scores of repeat participants to those of first time participants. Twenty-seven (37% female) laboratory residents provided 2-year assessment data over the 3-year span of the study. Second time performance revealed improvement from a mean score of 14 (standard error = 1.0) in the first year to 17.2 (SD = 0.9) in the second year, (F[1, 52] = 5.6, P = 0.022). Detailed analysis demonstrated improvement in performance for 3 grading criteria that were considered to be rule-based errors. There was no improvement in operative strategy errors. Analysis of longitudinal performance of laboratory residents shows higher scores for repeat participants in the category of rule-based errors. These findings suggest that laboratory residents can learn from rule-based mistakes when provided with annual performance-based assessments. This benefit was not seen with operative strategy errors and has important implications for

  10. Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

    Science.gov (United States)

    Zhang, W.; Li, X.; Xiao, W.

    2018-05-01

    The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the

  11. Selecting Tanker Steaming Speeds under Uncertainty: A Rule-Based Bayesian Reasoning Approach

    Directory of Open Access Journals (Sweden)

    N.S.F. Abdul Rahman

    2015-06-01

    Full Text Available In the tanker industry, there are a lot of uncertain conditions that tanker companies have to deal with. For example, the global financial crisis and economic recession, the increase of bunker fuel prices and global climate change. Such conditions have forced tanker companies to change tankers speed from full speed to slow speed, extra slow speed and super slow speed. Due to such conditions, the objective of this paper is to present a methodology for determining vessel speeds of tankers that minimize the cost of the vessels under such conditions. The four levels of vessel speed in the tanker industry will be investigated and will incorporate a number of uncertain conditions. This will be done by developing a scientific model using a rule-based Bayesian reasoning method. The proposed model has produced 96 rules that can be used as guidance in the decision making process. Such results help tanker companies to determine the appropriate vessel speed to be used in a dynamic operational environmental.

  12. Mining algorithm for association rules in big data based on Hadoop

    Science.gov (United States)

    Fu, Chunhua; Wang, Xiaojing; Zhang, Lijun; Qiao, Liying

    2018-04-01

    In order to solve the problem that the traditional association rules mining algorithm has been unable to meet the mining needs of large amount of data in the aspect of efficiency and scalability, take FP-Growth as an example, the algorithm is realized in the parallelization based on Hadoop framework and Map Reduce model. On the basis, it is improved using the transaction reduce method for further enhancement of the algorithm's mining efficiency. The experiment, which consists of verification of parallel mining results, comparison on efficiency between serials and parallel, variable relationship between mining time and node number and between mining time and data amount, is carried out in the mining results and efficiency by Hadoop clustering. Experiments show that the paralleled FP-Growth algorithm implemented is able to accurately mine frequent item sets, with a better performance and scalability. It can be better to meet the requirements of big data mining and efficiently mine frequent item sets and association rules from large dataset.

  13. A rule based method for context sensitive threshold segmentation in SPECT using simulation

    International Nuclear Information System (INIS)

    Fleming, John S.; Alaamer, Abdulaziz S.

    1998-01-01

    Robust techniques for automatic or semi-automatic segmentation of objects in single photon emission computed tomography (SPECT) are still the subject of development. This paper describes a threshold based method which uses empirical rules derived from analysis of computer simulated images of a large number of objects. The use of simulation allowed the factors affecting the threshold which correctly segmented objects to be investigated systematically. Rules could then be derived from these data to define the threshold in any particular context. The technique operated iteratively and calculated local context sensitive thresholds along radial profiles from the centre of gravity of the object. It was evaluated in a further series of simulated objects and in human studies, and compared to the use of a global fixed threshold. The method was capable of improving accuracy of segmentation and volume assessment compared to the global threshold technique. The improvements were greater for small volumes, shapes with large surface area to volume ratio, variable surrounding activity and non-uniform distributions. The method was applied successfully to simulated objects and human studies and is considered to be a significant advance on global fixed threshold techniques. (author)

  14. Agent-based simulation for evaluating flexible and agile business processes : Separating knowledge rules, process rules and information resources

    NARCIS (Netherlands)

    Gong, Y.; Janssen, M.

    2010-01-01

    In today’s ever changing environment organizations need flexibility and agility to be able to deal with changes. Flexibility is necessary to adapt to changes in their environment, whilst agility is needed to rapidly response to changing customer demands. In this paper a mechanism based on the

  15. A sharable cloud-based pancreaticoduodenectomy collaborative database for physicians: emphasis on security and clinical rule supporting.

    Science.gov (United States)

    Yu, Hwan-Jeu; Lai, Hong-Shiee; Chen, Kuo-Hsin; Chou, Hsien-Cheng; Wu, Jin-Ming; Dorjgochoo, Sarangerel; Mendjargal, Adilsaikhan; Altangerel, Erdenebaatar; Tien, Yu-Wen; Hsueh, Chih-Wen; Lai, Feipei

    2013-08-01

    Pancreaticoduodenectomy (PD) is a major operation with high complication rate. Thereafter, patients may develop morbidity because of the complex reconstruction and loss of pancreatic parenchyma. A well-designed database is very important to address both the short-term and long-term outcomes after PD. The objective of this research was to build an international PD database implemented with security and clinical rule supporting functions, which made the data-sharing easier and improve the accuracy of data. The proposed system is a cloud-based application. To fulfill its requirements, the system comprises four subsystems: a data management subsystem, a clinical rule supporting subsystem, a short message notification subsystem, and an information security subsystem. After completing the surgery, the physicians input the data retrospectively, which are analyzed to study factors associated with post-PD common complications (delayed gastric emptying and pancreatic fistula) to validate the clinical value of this system. Currently, this database contains data from nearly 500 subjects. Five medical centers in Taiwan and two cancer centers in Mongolia are participating in this study. A data mining model of the decision tree analysis showed that elderly patients (>76 years) with pylorus-preserving PD (PPPD) have higher proportion of delayed gastric emptying. About the pancreatic fistula, the data mining model of the decision tree analysis revealed that cases with non-pancreaticogastrostomy (PG) reconstruction - body mass index (BMI)>29.65 or PG reconstruction - BMI>23.7 - non-classic PD have higher proportion of pancreatic fistula after PD. The proposed system allows medical staff to collect and store clinical data in a cloud, sharing the data with other physicians in a secure manner to achieve collaboration in research. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  16. Scheduling rules to achieve lead-time targets in outpatient appointment systems

    OpenAIRE

    Sivakumar, Appa Iyer; Nguyen, Thu Ba Thi; Graves, Stephen C

    2015-01-01

    This paper considers how to schedule appointments for outpatients, for a clinic that is subject to appointment lead-time targets for both new and returning patients. We develop heuristic rules, which are the exact and relaxed appointment scheduling rules, to schedule each new patient appointment (only) in light of uncertainty about future arrivals. The scheduling rules entail two decisions. First, the rules need to determine whether or not a patient's request can be accepted; then, if the req...

  17. Study on the Method of Association Rules Mining Based on Genetic Algorithm and Application in Analysis of Seawater Samples

    Directory of Open Access Journals (Sweden)

    Qiuhong Sun

    2014-04-01

    Full Text Available Based on the data mining research, the data mining based on genetic algorithm method, the genetic algorithm is briefly introduced, while the genetic algorithm based on two important theories and theoretical templates principle implicit parallelism is also discussed. Focuses on the application of genetic algorithms for association rule mining method based on association rule mining, this paper proposes a genetic algorithm fitness function structure, data encoding, such as the title of the improvement program, in particular through the early issues study, proposed the improved adaptive Pc, Pm algorithm is applied to the genetic algorithm, thereby improving efficiency of the algorithm. Finally, a genetic algorithm based association rule mining algorithm, and be applied in sea water samples database in data mining and prove its effective.

  18. Fuzzy Logic Based Autonomous Traffic Control System

    Directory of Open Access Journals (Sweden)

    Muhammad ABBAS

    2012-01-01

    Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.

  19. Earthquake hazard assessment in the Zagros Orogenic Belt of Iran using a fuzzy rule-based model

    Science.gov (United States)

    Farahi Ghasre Aboonasr, Sedigheh; Zamani, Ahmad; Razavipour, Fatemeh; Boostani, Reza

    2017-08-01

    Producing accurate seismic hazard map and predicting hazardous areas is necessary for risk mitigation strategies. In this paper, a fuzzy logic inference system is utilized to estimate the earthquake potential and seismic zoning of Zagros Orogenic Belt. In addition to the interpretability, fuzzy predictors can capture both nonlinearity and chaotic behavior of data, where the number of data is limited. In this paper, earthquake pattern in the Zagros has been assessed for the intervals of 10 and 50 years using fuzzy rule-based model. The Molchan statistical procedure has been used to show that our forecasting model is reliable. The earthquake hazard maps for this area reveal some remarkable features that cannot be observed on the conventional maps. Regarding our achievements, some areas in the southern (Bandar Abbas), southwestern (Bandar Kangan) and western (Kermanshah) parts of Iran display high earthquake severity even though they are geographically far apart.

  20. Rules of thumb for assessing reductive dechlorination pathways of PCDDs in specific systems

    International Nuclear Information System (INIS)

    Lu Guining; Dang Zhi; Fennell, Donna E.; Huang Weilin; Li Zhong; Liu Congqiang

    2010-01-01

    This paper reports a theoretical validation and proposition of the reductive dechlorination pathways for polychlorinated dibenzo-p-dioxin (PCDD) congeners. Density functional theory (DFT) calculations were carried out at the B3LYP/6-31G(d) level for all PCDDs and Mulliken atomic charges on chlorine atoms were adopted as the probe of the dechlorination reaction activity. The experimentally substantiated dechlorination pathways of 1,2,3,4-tetrachlorodibenzo-p-dioxin (1,2,3,4-TCDD) and its daughter products in the presence of zero-valent zinc were validated and the complete pathway of dechlorination of octachlorodibenzo-p-dioxin (OCDD) was proposed. The proposed pathways were found to be consistent with anaerobic biotransformation of several PCDD congeners. Four rules of thumb arrived from this study include (1) the chlorine atoms in the longitudinal (1,4,6,9) positions are removed in preference to the chlorine atoms on lateral (2,3,7,8) positions; (2) the chlorine atom that has more neighboring chlorine atoms at ortho-, meta- and para-positions is to be eliminated; (3) reductive dechlorination prefers to take place on the benzene ring having more chlorine substitutions; and (4) a chlorine atom on the side of the longitudinal symmetry axis containing more chlorine atoms is preferentially eliminated. These rules of thumb can be conveniently used for rapidly predicting the major dechlorination pathway for a given PCDD in specific systems.